
Dang Nguyen
@dangnth97
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PhD Candidate @CS_UCLA | IMO 2015 Silver
Los Angeles, CA, USA
Joined March 2023
RT @jaseweston: š¤Introducing OptimalThinkingBench š¤.š: - Thinking LLMs use a lot of tokens & overthink; non-thinkinā¦.
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RT @pratyushmaini: 1/Pretraining is hitting a data wall; scaling raw web data alone leads to diminishing returns. Today @datologyai sharesā¦.
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RT @lyang36: šØ Olympiad math + AI:. We ran Googleās Gemini 2.5 Pro on the fresh IMO 2025 problems. With careful prompting and pipeline desiā¦.
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RT @lmthang: Very excited to share that an advanced version of Gemini Deep Think is the first to have achieved gold-medal level in the Inteā¦.
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RT @tungnd_13: š Introducing PhysiX: One of the first large-scale foundation models for physics simulations!. PhysiX is a 4.5B parameter moā¦.
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RT @nouhadziri: š¢ Can LLMs really reason outside the box in math? Or are they just remixing familiar strategies? . Remember DeepSeek R1, o1ā¦.
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RT @RyanHuynh1108: CVPR-bound! āļø. I'll be presenting CoLLM on Friday, 6/13 (Morning, #364) and looking for my next challenge as a full-timā¦.
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RT @xue_yihao65785: š Our paper āRepresentations Shape Weak-to-Strong Generalizationā is accepted at #ICML2025!.We study weak-to-strong genā¦.
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RT @xuandongzhao: š Excited to share the most inspiring work Iāve been part of this year:. "Learning to Reason without External Rewards"ā¦.
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RT @sjoshi804: #ICLR2025.Can you pre-train deep models with small, synthetic datasets? š¤Æ. We introduce the first effective dataset distillaā¦.
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š Achievement unlocked: having papers with all of my labmates and somehow all ended up at ICLR!. Iāll be presenting our work āMini-batch Coresets for Memory-efficient Language Model Training on Data Mixturesā at #ICLR2025 šøš¬. Come by and chat! š on Fri, Apr 25 | 10 AM GMT+8.
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RT @Yihe__Deng: šExcited to share our latest work: OpenVLThinker, an exploration into enhancing vision-language models with R1 reasoning caā¦.
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RT @Yihe__Deng: š¤ I just updated my repository of RL(HF) summary notes to include a growing exploration of new topics, specifically addingā¦.
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RT @duynguyen772: LLMs must be helpful, unbiased, etc. but optimizing for one attribute can hurt others. š We introduce MAT-Steer for stā¦.
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RT @lmthang: Excited to share details of AlphaGeometry2 (AG2), part of the system that achieved silver-medal standard at IMO 2024 last Julyā¦.
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RT @Yihe__Deng: New paper & model release!. Excited to introduce DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrailsā¦.
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RT @TheGradient: (1/2) Ever wondered why Sharpness-Aware Minimization (SAM) yields greater generalization gains in vision than in NLP? I'llā¦.
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RT @natolambert: Since everyone wants to learn RL for language models now post DeepSeek, reminder that I've been working on this book quietā¦.
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RT @WenhuChen: Everyone is talking about RL these days. But are we done with SFT? The answer is NO. If we revive SFT in another form, it caā¦.
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RT @behrouz_ali: Attention has been the key component for most advances in LLMs, but it canāt scale to long context. Does this mean we needā¦.
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