most citedEchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models

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cs.AI2026

ReMem: Rethinking Perception and Memory in Long-Context Recommendation Agents

Haohao Qu, Yongcheng Jing, Chun Hin Chan +3

Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative agents autonomously perceive ex…

cs.AI2026

Seeing Time: Benchmarking Chronological Reasoning and Shortcut Biases in Vision-Language Models

Haoyu Zhou, Qing Qing, Caichong Li +6

Recent advancements in Vision-Language Models (VLMs) have significantly enhanced their ability to interpret complex visual semantics, yet their capacity for chronological reasoning…

cs.AI2026

MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulation

Yu Zhao, Hao Guan, Yongcheng Jing +2

Large Language Models (LLMs) have shown strong potential in complex medical reasoning yet face diminishing gains under inference scaling laws. While existing studies augment LLMs w…

cs.AI2025

Benchmarking Reasoning Robustness in Large Language Models

Tong Yu, Yongcheng Jing, Xikun Zhang +6

Despite the recent success of large language models (LLMs) in reasoning such as DeepSeek, we for the first time identify a key dilemma in reasoning robustness and generalization: s…

cs.AI2025

Graph-Augmented Reasoning: Evolving Step-by-Step Knowledge Graph Retrieval for LLM Reasoning

Wenjie Wu, Yongcheng Jing, Yingjie Wang +2

Recent large language model (LLM) reasoning, despite its success, suffers from limited domain knowledge, susceptibility to hallucinations, and constrained reasoning depth, particul…

cs.AI2025

Dynamic Parallel Tree Search for Efficient LLM Reasoning

Yifu Ding, Wentao Jiang, Shunyu Liu +9

Tree of Thoughts (ToT) enhances Large Language Model (LLM) reasoning by structuring problem-solving as a spanning tree. However, recent methods focus on search accuracy while overl…