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20242026
most citedCausal Evaluation of Language Models

3 citations · 7 across the 22 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.CL2025

AutoTool: Dynamic Tool Selection and Integration for Agentic Reasoning

Jiaru Zou, Ling Yang, Yunzhe Qi +5

Agentic reinforcement learning has advanced large language models (LLMs) to reason through long chain-of-thought trajectories while interleaving external tool use. Existing approac…

cs.CV2025

CauSight: Learning to Supersense for Visual Causal Discovery

Yize Zhang, Meiqi Chen, Sirui Chen +4

Causal thinking enables humans to understand not just what is seen, but why it happens. To replicate this capability in modern AI systems, we introduce the task of visual causal di…

cs.CL2025

DEPO: Dual-Efficiency Preference Optimization for LLM Agents

Sirui Chen, Mengshi Zhao, Lei Xu +5

Recent advances in large language models (LLMs) have greatly improved their reasoning and decision-making abilities when deployed as agents. Richer reasoning, however, often comes…

cs.LG2025

NIRVANA: Structured Pruning Reimagined for Large Language Model Compression

Mengting Ai, Tianxin Wei, Sirui Chen +1

While structured pruning presents a highly effective pathway for accelerating Large Language Model (LLM) inference, existing methods frequently suffer from significant performance…

cs.AI2025

SafeWork-R1: Coevolving Safety and Intelligence under the AI-45 Law

Shanghai AI Lab, :, Yicheng Bao +115

We introduce SafeWork-R1, a cutting-edge multimodal reasoning model that demonstrates the coevolution of capabilities and safety. It is developed by our proposed SafeLadder framewo…

cs.CL2025

Synthesis by Design: Controlled Data Generation via Structural Guidance

Lei Xu, Sirui Chen, Yuxuan Huang +1

Mathematical reasoning remains challenging for LLMs due to complex logic and the need for precise computation. Existing methods enhance LLM reasoning by synthesizing datasets throu…