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cs.CL2026

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

Lizhe Fang, Weizhou Shen, Tianyi Tang +1

Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to long-context settings has emerged as an i…

cs.CL2026

Incentivizing In-depth Reasoning over Long Contexts with Process Advantage Shaping

Miao Peng, Weizhou Shen, Nuo Chen +3

Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective in enhancing LLMs short-context reasoning, but its performance degrades in long-context scenarios that re…

cs.CL2026

CorpusQA: A 10 Million Token Benchmark for Corpus-Level Analysis and Reasoning

Zhiyuan Lu, Chenliang Li, Yingcheng Shi +3

While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largely untested. Existing benchmarks are in…

cs.CL2025

QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management

Weizhou Shen, Ziyi Yang, Chenliang Li +11

We introduce QwenLong-L1.5, a model that achieves superior long-context reasoning capabilities through systematic post-training innovations. The key technical breakthroughs of Qwen…

cs.CL2025

Qwen3Guard Technical Report

Haiquan Zhao, Chenhan Yuan, Fei Huang +40

As large language models (LLMs) become more capable and widely used, ensuring the safety of their outputs is increasingly critical. Existing guardrail models, though useful in stat…

cs.CL2025

Tongyi DeepResearch Technical Report

Tongyi DeepResearch Team, Baixuan Li, Bo Zhang +54

We present Tongyi DeepResearch, an agentic large language model, which is specifically designed for long-horizon, deep information-seeking research tasks. To incentivize autonomous…