Viewing enriched Twitter post
Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective "We introduce GURU, a curated RL reasoning corpus of 92K verifiable examples spanning six reasoning domainsāMath, Code, Science, Logic, Simulation, and Tabularāeach built through domain-specificā¦ https://t.co/Toc6SAkTXA
{
"media": [
{
"type": "image",
"url": "https://crmoxkoizveukayfjuyo.supabase.co/storage/v1/object/public/media/posts/1935541889211453635/media_0.jpg?",
"filename": "media_0.jpg"
}
],
"nlp": {
"sentiment": "neutral",
"topics": [
"Reinforcement Learning",
"LLM Reasoning",
"Cross-Domain Perspective"
],
"entities": [],
"summary": "The tweet discusses the introduction of GURU, a curated RL reasoning corpus with examples across various reasoning domains.",
"language": "en",
"processed_at": "2025-08-07T11:07:24.907508"
}
}{
"data": {
"threaded_conversation_with_injections_v2": {
"instructions": [
{
"type": "TimelineClearCache"
},
{
"type": "TimelineAddEntries",
"entries": [
{
"entryId": "tweet-1935541889211453635",
"sortIndex": "1953503242587471872",
"content": {
"entryType": "TimelineTimelineItem",
"__typename": "TimelineTimelineItem",
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935541889211453635",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjo0NDE0NjU3NTE=",
"rest_id": "441465751",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": true,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": true,
"can_media_tag": true,
"created_at": "Tue Dec 20 03:45:50 +0000 2011",
"default_profile": false,
"default_profile_image": false,
"description": "CEO @SophontAI |\nPhD at 19 (2023) |\nFounder, ex CEO @MedARC_AI |\nex Research Director Stability AI | \nBiomed. engineer @ 14 |\nTEDx talkā”https://t.co/xPxwKTq6Qb",
"entities": {
"description": {
"urls": [
{
"display_url": "bit.ly/3tpAuan",
"expanded_url": "https://bit.ly/3tpAuan",
"url": "https://t.co/xPxwKTq6Qb",
"indices": [
136,
159
]
}
]
},
"url": {
"urls": [
{
"display_url": "sophontai.com",
"expanded_url": "https://sophontai.com",
"url": "https://t.co/uQ936JTZf1",
"indices": [
0,
23
]
}
]
}
},
"fast_followers_count": 0,
"favourites_count": 104318,
"followers_count": 79714,
"friends_count": 1237,
"has_custom_timelines": true,
"is_translator": false,
"listed_count": 1177,
"location": "",
"media_count": 2408,
"name": "Tanishq Mathew Abraham, Ph.D.",
"normal_followers_count": 79714,
"pinned_tweet_ids_str": [
"1952221233648718307"
],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/441465751/1738204246",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1913710019729821696/Qge4zx6u_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "iScienceLuvr",
"statuses_count": 17690,
"translator_type": "none",
"url": "https://t.co/uQ936JTZf1",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"professional": {
"rest_id": "1534109693131362304",
"professional_type": "Creator",
"category": [
{
"id": 713,
"name": "Science & Technology",
"icon_name": ""
}
]
},
"tipjar_settings": {}
}
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935541889211453635"
],
"editable_until_msecs": "1750307721000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "20320",
"state": "EnabledWithCount"
},
"source": "<a href=\"https://mobile.twitter.com\" rel=\"nofollow\">Twitter Web App</a>",
"note_tweet": {
"is_expandable": true,
"note_tweet_results": {
"result": {
"id": "Tm90ZVR3ZWV0OjE5MzU1NDE4ODkwODk4ODAwNjQ=",
"text": "Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective\n\n\"We introduce GURU, a curated RL reasoning corpus of 92K verifiable examples spanning six reasoning domainsāMath, Code, Science, Logic, Simulation, and Tabularāeach built through domain-specific reward design, deduplication, and filtering to ensure reliability and effectiveness for RL training. \"\n\n\"Domains frequently seen during pretraining (Math, Code, Science) easily benefit from cross-domain RL training, while domains with limited pretraining exposure (Logic, Simulation, Tabular) require in-domain training to achieve meaningful performance gains, suggesting that RL is likely to facilitate genuine skill acquisition.\"",
"entity_set": {
"hashtags": [],
"symbols": [],
"urls": [],
"user_mentions": []
},
"richtext": {
"richtext_tags": []
},
"media": {
"inline_media": []
}
}
}
},
"legacy": {
"bookmark_count": 168,
"bookmarked": false,
"created_at": "Thu Jun 19 03:35:21 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
0,
280
],
"entities": {
"hashtags": [],
"media": [
{
"display_url": "pic.x.com/Toc6SAkTXA",
"expanded_url": "https://x.com/iScienceLuvr/status/1935541889211453635/photo/1",
"id_str": "1935541817426198530",
"indices": [
281,
304
],
"media_key": "3_1935541817426198530",
"media_url_https": "https://pbs.twimg.com/media/GtxtByuaQAIEwql.jpg",
"type": "photo",
"url": "https://t.co/Toc6SAkTXA",
"ext_media_availability": {
"status": "Available"
},
"features": {
"large": {
"faces": []
},
"medium": {
"faces": []
},
"small": {
"faces": []
},
"orig": {
"faces": []
}
},
"sizes": {
"large": {
"h": 1564,
"w": 1207,
"resize": "fit"
},
"medium": {
"h": 1200,
"w": 926,
"resize": "fit"
},
"small": {
"h": 680,
"w": 525,
"resize": "fit"
},
"thumb": {
"h": 150,
"w": 150,
"resize": "crop"
}
},
"original_info": {
"height": 1564,
"width": 1207,
"focus_rects": [
{
"x": 0,
"y": 0,
"w": 1207,
"h": 676
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1207
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1376
},
{
"x": 0,
"y": 0,
"w": 782,
"h": 1564
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1564
}
]
},
"allow_download_status": {
"allow_download": true
},
"media_results": {
"result": {
"media_key": "3_1935541817426198530"
}
}
}
],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": []
},
"extended_entities": {
"media": [
{
"display_url": "pic.x.com/Toc6SAkTXA",
"expanded_url": "https://x.com/iScienceLuvr/status/1935541889211453635/photo/1",
"id_str": "1935541817426198530",
"indices": [
281,
304
],
"media_key": "3_1935541817426198530",
"media_url_https": "https://pbs.twimg.com/media/GtxtByuaQAIEwql.jpg",
"type": "photo",
"url": "https://t.co/Toc6SAkTXA",
"ext_media_availability": {
"status": "Available"
},
"features": {
"large": {
"faces": []
},
"medium": {
"faces": []
},
"small": {
"faces": []
},
"orig": {
"faces": []
}
},
"sizes": {
"large": {
"h": 1564,
"w": 1207,
"resize": "fit"
},
"medium": {
"h": 1200,
"w": 926,
"resize": "fit"
},
"small": {
"h": 680,
"w": 525,
"resize": "fit"
},
"thumb": {
"h": 150,
"w": 150,
"resize": "crop"
}
},
"original_info": {
"height": 1564,
"width": 1207,
"focus_rects": [
{
"x": 0,
"y": 0,
"w": 1207,
"h": 676
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1207
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1376
},
{
"x": 0,
"y": 0,
"w": 782,
"h": 1564
},
{
"x": 0,
"y": 0,
"w": 1207,
"h": 1564
}
]
},
"allow_download_status": {
"allow_download": true
},
"media_results": {
"result": {
"media_key": "3_1935541817426198530"
}
}
}
]
},
"favorite_count": 221,
"favorited": false,
"full_text": "Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective\n\n\"We introduce GURU, a curated RL reasoning corpus of 92K verifiable examples spanning six reasoning domainsāMath, Code, Science, Logic, Simulation, and Tabularāeach built through domain-specificā¦ https://t.co/Toc6SAkTXA",
"is_quote_status": false,
"lang": "en",
"possibly_sensitive": false,
"possibly_sensitive_editable": true,
"quote_count": 4,
"reply_count": 7,
"retweet_count": 45,
"retweeted": false,
"user_id_str": "441465751",
"id_str": "1935541889211453635"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "SelfThread"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet"
}
}
},
{
"entryId": "conversationthread-1935541891527012547",
"sortIndex": "1953503242587471862",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935541891527012547-tweet-1935541891527012547",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935541891527012547",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjo0NDE0NjU3NTE=",
"rest_id": "441465751",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": true,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": true,
"can_media_tag": true,
"created_at": "Tue Dec 20 03:45:50 +0000 2011",
"default_profile": false,
"default_profile_image": false,
"description": "CEO @SophontAI |\nPhD at 19 (2023) |\nFounder, ex CEO @MedARC_AI |\nex Research Director Stability AI | \nBiomed. engineer @ 14 |\nTEDx talkā”https://t.co/xPxwKTq6Qb",
"entities": {
"description": {
"urls": [
{
"display_url": "bit.ly/3tpAuan",
"expanded_url": "https://bit.ly/3tpAuan",
"url": "https://t.co/xPxwKTq6Qb",
"indices": [
136,
159
]
}
]
},
"url": {
"urls": [
{
"display_url": "sophontai.com",
"expanded_url": "https://sophontai.com",
"url": "https://t.co/uQ936JTZf1",
"indices": [
0,
23
]
}
]
}
},
"fast_followers_count": 0,
"favourites_count": 104318,
"followers_count": 79714,
"friends_count": 1237,
"has_custom_timelines": true,
"is_translator": false,
"listed_count": 1177,
"location": "",
"media_count": 2408,
"name": "Tanishq Mathew Abraham, Ph.D.",
"normal_followers_count": 79714,
"pinned_tweet_ids_str": [
"1952221233648718307"
],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/441465751/1738204246",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1913710019729821696/Qge4zx6u_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "iScienceLuvr",
"statuses_count": 17690,
"translator_type": "none",
"url": "https://t.co/uQ936JTZf1",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"professional": {
"rest_id": "1534109693131362304",
"professional_type": "Creator",
"category": [
{
"id": 713,
"name": "Science & Technology",
"icon_name": ""
}
]
},
"tipjar_settings": {}
}
}
},
"card": {
"rest_id": "https://t.co/XyZM4o5HIX",
"legacy": {
"binding_values": [
{
"key": "description",
"value": {
"string_value": "Reinforcement learning (RL) has emerged as a promising approach to improve large language model (LLM) reasoning, yet most open efforts focus narrowly on math and code, limiting our understanding...",
"type": "STRING"
}
},
{
"key": "domain",
"value": {
"string_value": "arxiv.org",
"type": "STRING"
}
},
{
"key": "site",
"value": {
"scribe_key": "publisher_id",
"type": "USER",
"user_value": {
"id_str": "808633423300624384",
"path": []
}
}
},
{
"key": "thumbnail_image_alt_text",
"value": {
"string_value": "arXiv logo",
"type": "STRING"
}
},
{
"key": "vanity_url",
"value": {
"scribe_key": "vanity_url",
"string_value": "arxiv.org",
"type": "STRING"
}
},
{
"key": "title",
"value": {
"string_value": "Revisiting Reinforcement Learning for LLM Reasoning from A...",
"type": "STRING"
}
},
{
"key": "card_url",
"value": {
"scribe_key": "card_url",
"string_value": "https://t.co/XyZM4o5HIX",
"type": "STRING"
}
}
],
"card_platform": {
"platform": {
"audience": {
"name": "production"
},
"device": {
"name": "Android",
"version": "12"
}
}
},
"name": "summary",
"url": "https://t.co/XyZM4o5HIX",
"user_refs_results": [
{
"result": {
"__typename": "User",
"id": "VXNlcjo4MDg2MzM0MjMzMDA2MjQzODQ=",
"rest_id": "808633423300624384",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": false,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": true,
"can_media_tag": true,
"created_at": "Tue Dec 13 11:23:26 +0000 2016",
"default_profile": false,
"default_profile_image": false,
"description": "News from https://t.co/enurGFxpcS, a free distribution service and an open archive for scholarly articles.\n\nFor help with arXiv, see https://t.co/LcWuhM0BOl",
"entities": {
"description": {
"urls": [
{
"display_url": "arXiv.org",
"expanded_url": "http://arXiv.org",
"url": "https://t.co/enurGFxpcS",
"indices": [
10,
33
]
},
{
"display_url": "arxiv.org/help",
"expanded_url": "https://arxiv.org/help",
"url": "https://t.co/LcWuhM0BOl",
"indices": [
133,
156
]
}
]
},
"url": {
"urls": [
{
"display_url": "arxiv.org",
"expanded_url": "https://arxiv.org/",
"url": "https://t.co/DHMkdi4lF9",
"indices": [
0,
23
]
}
]
}
},
"fast_followers_count": 0,
"favourites_count": 948,
"followers_count": 41364,
"friends_count": 187,
"has_custom_timelines": false,
"is_translator": false,
"listed_count": 487,
"location": "Ithaca, NY",
"media_count": 109,
"name": "arXiv.org",
"normal_followers_count": 41364,
"pinned_tweet_ids_str": [],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/808633423300624384/1481635469",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1365352170267299840/IzvjKckL_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "arxiv",
"statuses_count": 1106,
"translator_type": "none",
"url": "https://t.co/DHMkdi4lF9",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"tipjar_settings": {}
}
}
]
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935541891527012547"
],
"editable_until_msecs": "1750307722000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "2604",
"state": "EnabledWithCount"
},
"source": "<a href=\"https://mobile.twitter.com\" rel=\"nofollow\">Twitter Web App</a>",
"legacy": {
"bookmark_count": 4,
"bookmarked": false,
"created_at": "Thu Jun 19 03:35:22 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
0,
28
],
"entities": {
"hashtags": [],
"symbols": [],
"timestamps": [],
"urls": [
{
"display_url": "arxiv.org/abs/2506.14965",
"expanded_url": "https://arxiv.org/abs/2506.14965",
"url": "https://t.co/XyZM4o5HIX",
"indices": [
5,
28
]
}
],
"user_mentions": []
},
"favorite_count": 13,
"favorited": false,
"full_text": "abs: https://t.co/XyZM4o5HIX",
"in_reply_to_screen_name": "iScienceLuvr",
"in_reply_to_status_id_str": "1935541889211453635",
"in_reply_to_user_id_str": "441465751",
"is_quote_status": false,
"lang": "und",
"possibly_sensitive": false,
"possibly_sensitive_editable": true,
"quote_count": 0,
"reply_count": 0,
"retweet_count": 2,
"retweeted": false,
"user_id_str": "441465751",
"id_str": "1935541891527012547"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "SelfThread"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935541891527012547"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "conversationthread-1935754357007593598",
"sortIndex": "1953503242587471852",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935754357007593598-tweet-1935754357007593598",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935754357007593598",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjoxNzYzMzAyOTk4OTgwNDE1NDg4",
"rest_id": "1763302998980415488",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": true,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": false,
"can_media_tag": true,
"created_at": "Thu Feb 29 20:39:56 +0000 2024",
"default_profile": true,
"default_profile_image": false,
"description": "CTO @ Series Entertainment, ex-Google",
"entities": {
"description": {
"urls": []
},
"url": {
"urls": [
{
"display_url": "medium.com/@jengas",
"expanded_url": "https://medium.com/@jengas",
"url": "https://t.co/luOqbtoLLR",
"indices": [
0,
23
]
}
]
}
},
"fast_followers_count": 0,
"favourites_count": 791,
"followers_count": 122,
"friends_count": 232,
"has_custom_timelines": false,
"is_translator": false,
"listed_count": 2,
"location": "",
"media_count": 81,
"name": "Josh English",
"normal_followers_count": 122,
"pinned_tweet_ids_str": [
"1932921784833380769"
],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/1763302998980415488/1749436642",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1763303108887912448/odv7CBeR_normal.png",
"profile_interstitial_type": "",
"screen_name": "JoshSeriesAI",
"statuses_count": 858,
"translator_type": "none",
"url": "https://t.co/luOqbtoLLR",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"tipjar_settings": {}
}
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935754357007593598"
],
"editable_until_msecs": "1750358377000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "123",
"state": "EnabledWithCount"
},
"source": "<a href=\"https://mobile.twitter.com\" rel=\"nofollow\">Twitter Web App</a>",
"note_tweet": {
"is_expandable": true,
"note_tweet_results": {
"result": {
"id": "Tm90ZVR3ZWV0OjE5MzU3NTQzNTY5MzIxNDUxNTI=",
"text": "This GURU corpus looks like a critical step for RL in LLM reasoning. It's a constant tension: academic rigor provides the deep, verifiable insights and theoretical proofs, while private labs leverage unparalleled scale to push capabilities to the extreme.\n\nBoth are essential, but the real magic is often at their intersection",
"entity_set": {
"hashtags": [],
"symbols": [],
"urls": [],
"user_mentions": []
},
"richtext": {
"richtext_tags": []
},
"media": {
"inline_media": []
}
}
}
},
"legacy": {
"bookmark_count": 0,
"bookmarked": false,
"created_at": "Thu Jun 19 17:39:37 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
14,
295
],
"entities": {
"hashtags": [],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": [
{
"id_str": "441465751",
"name": "Tanishq Abraham is at ICML",
"screen_name": "iScienceLuvr",
"indices": [
0,
13
]
}
]
},
"favorite_count": 0,
"favorited": false,
"full_text": "@iScienceLuvr This GURU corpus looks like a critical step for RL in LLM reasoning. It's a constant tension: academic rigor provides the deep, verifiable insights and theoretical proofs, while private labs leverage unparalleled scale to push capabilities to the extreme.\n\nBoth are essential, butā¦",
"in_reply_to_screen_name": "iScienceLuvr",
"in_reply_to_status_id_str": "1935541889211453635",
"in_reply_to_user_id_str": "441465751",
"is_quote_status": false,
"lang": "en",
"quote_count": 0,
"reply_count": 0,
"retweet_count": 0,
"retweeted": false,
"user_id_str": "1763302998980415488",
"id_str": "1935754357007593598"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "Tweet"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935754357007593598"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "conversationthread-1935708659444777028",
"sortIndex": "1953503242587471842",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935708659444777028-tweet-1935708659444777028",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935708659444777028",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjoxNzg5NjUwOTIyNTM4MTkyODk3",
"rest_id": "1789650922538192897",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": true,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": true,
"can_media_tag": false,
"created_at": "Sun May 12 13:37:04 +0000 2024",
"default_profile": true,
"default_profile_image": false,
"description": "As long as I offer an abundance of solutions in artificial intelligence, so long Iām alive; a lack of solutions will foreshadow my extinction.",
"entities": {
"description": {
"urls": []
}
},
"fast_followers_count": 0,
"favourites_count": 576,
"followers_count": 397,
"friends_count": 1015,
"has_custom_timelines": false,
"is_translator": false,
"listed_count": 5,
"location": "Bhubaneswar ",
"media_count": 90,
"name": "Bhaktavaschal Samal",
"normal_followers_count": 397,
"pinned_tweet_ids_str": [],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/1789650922538192897/1730621612",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1924078853154127872/DiGiFBBA_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "BhaktaVee",
"statuses_count": 4860,
"translator_type": "none",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"professional": {
"rest_id": "1872562370532332023",
"professional_type": "Business",
"category": [
{
"id": 1047,
"name": "Computer scientist",
"icon_name": ""
}
]
},
"tipjar_settings": {}
}
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935708659444777028"
],
"editable_until_msecs": "1750347482000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "141",
"state": "EnabledWithCount"
},
"source": "<a href=\"https://mobile.twitter.com\" rel=\"nofollow\">Twitter Web App</a>",
"note_tweet": {
"is_expandable": true,
"note_tweet_results": {
"result": {
"id": "Tm90ZVR3ZWV0OjE5MzU3MDg2NTkyNjQ0MDk2MDE=",
"text": "big question Tanishq, whether rl teaches new reasoning skills or merely elicits existing knowledge that may not generalize across other domains. \n\nthe approach produces models that excel only within their specialized training domains, limiting both our understanding of how RL enables reasoning and practical performance gains across diverse reasoning tasks\n\nthere is another issue rl based reasoning in large language models proves highly domain-dependent, while familiar areas like math, code, and science gain from cross-domain RL, whereas less common domains (logic, simulation, tabular) require in-domain rl to see real improvements. research.\n\nthe authors concede that prior work suggests rl primarily elicits existing knowledge from pretrained models rather than learning new capabilities, even with indirect or minimal elicitation like wrong or random labels or even performing RL from a single example \n\nperformance gains from cross-domain RL training (warm colors on non-diagonal cells), indicating reasoning capabilities are more easily elicited in these domains even with cross-domain data\n\nthis says that pretraining is primarily responsible for llm reasoning, what role exactly play still remains the least understood as we have no excess to the training data \n\ncan we design RL protocols that reliably create new reasoning primitives, rather than just draw out pre-existing ones?",
"entity_set": {
"hashtags": [],
"symbols": [],
"urls": [],
"user_mentions": []
},
"richtext": {
"richtext_tags": []
},
"media": {
"inline_media": []
}
}
}
},
"legacy": {
"bookmark_count": 0,
"bookmarked": false,
"created_at": "Thu Jun 19 14:38:02 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
14,
291
],
"entities": {
"hashtags": [],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": [
{
"id_str": "441465751",
"name": "Tanishq Abraham is at ICML",
"screen_name": "iScienceLuvr",
"indices": [
0,
13
]
}
]
},
"favorite_count": 0,
"favorited": false,
"full_text": "@iScienceLuvr big question Tanishq, whether rl teaches new reasoning skills or merely elicits existing knowledge that may not generalize across other domains. \n\nthe approach produces models that excel only within their specialized training domains, limiting both our understanding of how RLā¦",
"in_reply_to_screen_name": "iScienceLuvr",
"in_reply_to_status_id_str": "1935541889211453635",
"in_reply_to_user_id_str": "441465751",
"is_quote_status": false,
"lang": "en",
"quote_count": 0,
"reply_count": 0,
"retweet_count": 0,
"retweeted": false,
"user_id_str": "1789650922538192897",
"id_str": "1935708659444777028"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "Tweet"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935708659444777028"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "conversationthread-1935562624134946819",
"sortIndex": "1953503242587471832",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935562624134946819-tweet-1935562624134946819",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "TweetTombstone",
"tombstone": {
"__typename": "TextTombstone",
"text": {
"rtl": false,
"text": "This Post is unavailable. Learn more",
"entities": [
{
"fromIndex": 26,
"toIndex": 36,
"ref": {
"type": "TimelineUrl",
"url": "https://help.twitter.com/rules-and-policies/notices-on-twitter",
"urlType": "ExternalUrl"
}
}
]
}
}
}
},
"tweetDisplayType": "Tweet"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935562624134946819"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "conversationthread-1935575878622404839",
"sortIndex": "1953503242587471822",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935575878622404839-tweet-1935575878622404839",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935575878622404839",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjozNjAxNTI0Njgz",
"rest_id": "3601524683",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": false,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": true,
"can_media_tag": true,
"created_at": "Wed Sep 09 19:38:05 +0000 2015",
"default_profile": false,
"default_profile_image": false,
"description": "Senior Research Scientist @MBZUAI, interested in Decision Making & Generalization // @BYU '13; @Harvard '17; @UofT '24",
"entities": {
"description": {
"urls": []
},
"url": {
"urls": [
{
"display_url": "twkillian.github.io",
"expanded_url": "http://twkillian.github.io",
"url": "https://t.co/hq62ePQHOo",
"indices": [
0,
23
]
}
]
}
},
"fast_followers_count": 0,
"favourites_count": 80002,
"followers_count": 2542,
"friends_count": 869,
"has_custom_timelines": true,
"is_translator": false,
"listed_count": 33,
"location": "Bay Area, CA",
"media_count": 690,
"name": "Taylor W. Killian",
"normal_followers_count": 2542,
"pinned_tweet_ids_str": [
"1945871359869141064"
],
"possibly_sensitive": false,
"profile_banner_url": "https://pbs.twimg.com/profile_banners/3601524683/1741393585",
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1802797321102753792/FUo2t-xc_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "tw_killian",
"statuses_count": 5778,
"translator_type": "none",
"url": "https://t.co/hq62ePQHOo",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"tipjar_settings": {}
}
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935575878622404839"
],
"editable_until_msecs": "1750315825000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "353",
"state": "EnabledWithCount"
},
"source": "<a href=\"http://twitter.com/download/iphone\" rel=\"nofollow\">Twitter for iPhone</a>",
"legacy": {
"bookmark_count": 0,
"bookmarked": false,
"created_at": "Thu Jun 19 05:50:25 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
14,
152
],
"entities": {
"hashtags": [],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": [
{
"id_str": "441465751",
"name": "Tanishq Abraham is at ICML",
"screen_name": "iScienceLuvr",
"indices": [
0,
13
]
},
{
"id_str": "1240612837895966720",
"name": "Shibo Hao",
"screen_name": "Ber18791531",
"indices": [
126,
138
]
},
{
"id_str": "1462759457528553482",
"name": "Zhoujun (Jorge) Cheng",
"screen_name": "ChengZhoujun",
"indices": [
139,
152
]
}
]
},
"favorite_count": 5,
"favorited": false,
"full_text": "@iScienceLuvr Thanks for the RT! Weāre really proud of this work and are excited for what weāll see people build with it. cc. @Ber18791531 @ChengZhoujun",
"in_reply_to_screen_name": "iScienceLuvr",
"in_reply_to_status_id_str": "1935541889211453635",
"in_reply_to_user_id_str": "441465751",
"is_quote_status": false,
"lang": "en",
"quote_count": 0,
"reply_count": 0,
"retweet_count": 0,
"retweeted": false,
"user_id_str": "3601524683",
"id_str": "1935575878622404839"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "Tweet"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935575878622404839"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "conversationthread-1935769778511110503",
"sortIndex": "1953503242587471812",
"content": {
"entryType": "TimelineTimelineModule",
"__typename": "TimelineTimelineModule",
"items": [
{
"entryId": "conversationthread-1935769778511110503-tweet-1935769778511110503",
"item": {
"itemContent": {
"itemType": "TimelineTweet",
"__typename": "TimelineTweet",
"tweet_results": {
"result": {
"__typename": "Tweet",
"rest_id": "1935769778511110503",
"has_birdwatch_notes": false,
"core": {
"user_results": {
"result": {
"__typename": "User",
"id": "VXNlcjoxODQ0OTc4NDE1OTQ0MDQ0NTQ0",
"rest_id": "1844978415944044544",
"affiliates_highlighted_label": {},
"has_graduated_access": true,
"is_blue_verified": false,
"profile_image_shape": "Circle",
"legacy": {
"can_dm": false,
"can_media_tag": true,
"created_at": "Sat Oct 12 05:48:40 +0000 2024",
"default_profile": true,
"default_profile_image": false,
"description": "",
"entities": {
"description": {
"urls": []
}
},
"fast_followers_count": 0,
"favourites_count": 46,
"followers_count": 0,
"friends_count": 1,
"has_custom_timelines": false,
"is_translator": false,
"listed_count": 0,
"location": "",
"media_count": 0,
"name": "š",
"normal_followers_count": 0,
"pinned_tweet_ids_str": [],
"possibly_sensitive": false,
"profile_image_url_https": "https://pbs.twimg.com/profile_images/1935766242666729473/OABsqmBn_normal.jpg",
"profile_interstitial_type": "",
"screen_name": "virtualerosjazz",
"statuses_count": 4,
"translator_type": "none",
"verified": false,
"want_retweets": false,
"withheld_in_countries": []
},
"tipjar_settings": {
"is_enabled": true
}
}
}
},
"unmention_data": {},
"edit_control": {
"edit_tweet_ids": [
"1935769778511110503"
],
"editable_until_msecs": "1750362054000",
"is_edit_eligible": false,
"edits_remaining": "5"
},
"is_translatable": false,
"views": {
"count": "55",
"state": "EnabledWithCount"
},
"source": "<a href=\"http://twitter.com/download/android\" rel=\"nofollow\">Twitter for Android</a>",
"legacy": {
"bookmark_count": 0,
"bookmarked": false,
"created_at": "Thu Jun 19 18:40:54 +0000 2025",
"conversation_id_str": "1935541889211453635",
"display_text_range": [
14,
74
],
"entities": {
"hashtags": [
{
"indices": [
52,
74
],
"text": "reinforcementlearning"
}
],
"symbols": [],
"timestamps": [],
"urls": [],
"user_mentions": [
{
"id_str": "441465751",
"name": "Tanishq Abraham is at ICML",
"screen_name": "iScienceLuvr",
"indices": [
0,
13
]
}
]
},
"favorite_count": 0,
"favorited": false,
"full_text": "@iScienceLuvr Ofc mistakes will definitely pay off #reinforcementlearning",
"in_reply_to_screen_name": "iScienceLuvr",
"in_reply_to_status_id_str": "1935541889211453635",
"in_reply_to_user_id_str": "441465751",
"is_quote_status": false,
"lang": "en",
"quote_count": 0,
"reply_count": 0,
"retweet_count": 0,
"retweeted": false,
"user_id_str": "1844978415944044544",
"id_str": "1935769778511110503"
},
"quick_promote_eligibility": {
"eligibility": "IneligibleNotProfessional"
}
}
},
"tweetDisplayType": "Tweet"
},
"clientEventInfo": {
"component": "tweet",
"element": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
}
],
"metadata": {
"conversationMetadata": {
"allTweetIds": [
"1935769778511110503"
],
"enableDeduplication": true
}
},
"displayType": "VerticalConversation",
"clientEventInfo": {
"component": "tweet",
"details": {
"conversationDetails": {
"conversationSection": "HighQuality"
},
"timelinesDetails": {
"controllerData": "DAACDAAEDAABCgABAAAAAAAAAAEKAAIAAAAAAAAAAAAAAAA="
}
}
}
}
},
{
"entryId": "cursor-showmorethreads-1953503242587471811",
"sortIndex": "1953503242587471811",
"content": {
"entryType": "TimelineTimelineCursor",
"__typename": "TimelineTimelineCursor",
"value": "DAAFCgABGxw82Vn__8ELAAIAAABoRW1QQzZ3QUFBZlEvZ0dKTjB2R3AvQUFBQUFjYTNTNVU1ZG93ZmhyY2YvT2NGaUFER3R4dEdHeGE4TU1hM1R4YmZ4ZGhaeHJjYlJmaVZsRERHdDBFeFJyYWdFUWEzSXdCcVJwZzV3PT0IAAMAAAAHAAA",
"cursorType": "ShowMoreThreads",
"displayTreatment": {
"actionText": "Show probable spam"
}
}
}
]
},
{
"type": "TimelineTerminateTimeline",
"direction": "Top"
}
],
"metadata": {
"reader_mode_config": {
"is_reader_mode_available": true
},
"scribeConfig": {
"page": "ranked_replies"
}
}
}
}
}