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Wei Shen

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.LG2
same name
  • Wei Shen — 35 papers, h 39
  • Wei Shen — 12 papers
  • Wei Shen — 7 papers
  • Wei Shen — 6 papers, h 7
  • Wei Shen — 5 papers
  • Wei Shen — 5 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSeed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2025

Joint Enhancement of Relational Reasoning for Long-Context LLMs

Zhirui Chen, Wei Shen, Jiashui Huang +1

Despite significant progress, large language models (LLMs) still struggle with long contexts due to memory limitations and their inability to tackle complex and long-context tasks.…

cs.LG2025

AdaCoT: Pareto-Optimal Adaptive Chain-of-Thought Triggering via Reinforcement Learning

Chenwei Lou, Zewei Sun, Xinnian Liang +6

Large Language Models (LLMs) have demonstrated remarkable capabilities but often face challenges with tasks requiring sophisticated reasoning. While Chain-of-Thought (CoT) promptin…

cs.CL2025★ 1 cited

Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning

ByteDance Seed, :, Jiaze Chen +267

We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…

cs.LG2025

Exploring Data Scaling Trends and Effects in Reinforcement Learning from Human Feedback

Wei Shen, Guanlin Liu, Zheng Wu +5

Reinforcement Learning from Human Feedback (RLHF) is crucial for aligning large language models with human preferences. While recent research has focused on algorithmic improvement…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.