Rui Wang @wangrui_nlp
A computational linguist working at SJTU (21-) and NICT (16-20). wangruinlp.github.io Shanghai China Joined February 2013-
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Can draft models predict their own failures to supercharge LLM inference? 🤖🚀 Introducing SVIP: a training-free, entropy-driven length policy that lets the draft model self-verify and decide when to stop drafting during long-form and reasoning-heavy generation. #EMNLP2025…
Just stumbled upon an interesting finding: 16.8% of the outputs from the simple ASDIV dataset using DeepSeek-R1-0528 include the new thinking sentence "I think I'm overthinking it.". Seems like our overthinking work (accepted by #ICML2025) might be having a subtle impact after…
Just stumbled upon an interesting finding: 16.8% of the outputs from the simple ASDIV dataset using DeepSeek-R1-0528 include the new thinking sentence "I think I'm overthinking it.". Seems like our overthinking work (accepted by #ICML2025) might be having a subtle impact after… https://t.co/IXwjPgB4EZ
🚨 Announcing DeepTheorem: Revolutionizing LLM Mathematical Reasoning! 🚀 𝕋𝕃𝔻ℝ: - 🌟 Learning by exploration is the most important rationale that recent RL-zero training teaches us since self-exploration significantly boosts the utilization of LLM pre-training knowledge; -…
arxiv.org/abs/2505.13182 Information Science Principles of Machine Learning:A Causal Chain Meta-Framework Based on Formalized Information Mapping
@_akhaliq Great work! Our recent research explored a similar direction. We proposed PolyMath, a more difficult multilingual math benchmark with broader domain and language coverage. Based on it, we found several insights, such as “problem–thinking language consistency”, “the effect of…
💡How can language models tackle challenging mathematical reasoning problems in multilingual contexts? We introduce PolyMath, a multilingual mathematical reasoning benchmark covering 18 languages and 4 easy-to-hard difficulty levels, with 9,000 high-quality problem samples in…
We posted a multilingual math benchmark with Qwen Team!
The presentations from our lab in ICLR-2025. The last one is a spotlight presentation.
The presentations from our lab in ICLR-2025. The last one is a spotlight presentation.
Really excited to see DeepMath-103K is now the top trending dataset on Hugging Face. huggingface.co/datasets
We Investigated the overthinking phenomenon in LLM together with Tencent three months ago.
We Investigated the overthinking phenomenon in LLM together with Tencent three months ago.
Our new math benchmark with Tencent!
Are scalar verifiers limiting LLM reasoning? Introducing PANEL, our novel inference time scaling framework that incorporates rich natural language (NL) self-critique to guide step-level search in reasoning tasks, moving beyond traditional scalar correctness scores. 🪡 By…
Are o1-like LLMs thinking deeply enough? Introducing a comprehensive study on the prevalent issue of underthinking in o1-like models, where models prematurely abandon promising lines of reasoning, leading to inadequate depth of thought. 🪡 Through extensive analyses, we found…
Thank you for recommending our overthinking work. Efficiency is equally important as effectiveness in optimizing model performance. This paper is the first step in what we hope will be a long and fruitful journey.
Thank you for recommending our overthinking work. Efficiency is equally important as effectiveness in optimizing model performance. This paper is the first step in what we hope will be a long and fruitful journey.
Are we scaling test-time compute efficiently and intelligently? Introducing a comprehensive study on the prevalent issue of overthinking in o1-like models, where excessive computational resources are allocated for simple problems with minimal benefit. 🪡Across extensive…
Regret being unable to attend #NeurIPS2024 in person due to visa issues... but the poster will be there! Feel free to discuss our work on Out-of-Distribution (OOD) Detection in Mathematical scenarios --- What kind of sparks will be ignited between new scenarios and old themes?
NICT先進的翻訳技術研究室:att-astrec.nict.go.jp/member/ では継続的にインターンを受け入れていますので、ご興味のある方はご連絡ください。

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