activity
20242026
most citedMind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia

3 citations · 4 across the 11 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Reasoning with Memory: A Temporal Granularity-Adaptive Framework for Training-Free Long Video Understanding

Linghao Meng, Qiankun Li, Junyuan Mao +7

While Multimodal Large Language Models (MLLMs) demonstrate superior generalization in fundamental video tasks, restricted context windows limit their long video understanding. To a…

cs.CV2026

Dual-Adaptive SAM3: Hierarchical Routing over Low-Rank Expert Layers for Parameter-Efficient Medical Image Segmentation

Ying Chen, Jinyue Li, Kun Wang +2

The Segment Anything Model with Concepts (SAM3) heralds a new paradigm for open-vocabulary segmentation through natural language interaction, offering significant potential for med…

cs.HC2026★ 1 cited

NeuroPath: Practically Adopting Motor Imagery Decoding through EEG Signals

Jiani Cao, Kun Wang, Yang Liu +1

Motor Imagery (MI) is an emerging Brain-Computer Interface (BCI) paradigm where a person imagines body movements without physical action. By decoding scalp-recorded electroencephal…

cs.CV2026

Granulon: Awakening Pixel-Level Visual Encoders with Adaptive Multi-Granularity Semantics for MLLM

Junyuan Mao, Qiankun Li, Linghao Meng +5

Recent advances in multimodal large language models largely rely on CLIP-based visual encoders, which emphasize global semantic alignment but struggle with fine-grained visual unde…

cs.LG2026

SaFeR-ToolKit: Structured Reasoning via Virtual Tool Calling for Multimodal Safety

Zixuan Xu, Tiancheng He, Huahui Yi +7

Vision-language models remain susceptible to multimodal jailbreaks and over-refusal because safety hinges on both visual evidence and user intent, while many alignment pipelines su…

cs.AI2026

PathMem: Toward Cognition-Aligned Memory Transformation for Pathology MLLMs

Jinyue Li, Yuci Liang, Qiankun Li +7

Computational pathology demands both visual pattern recognition and dynamic integration of structured domain knowledge, including taxonomy, grading criteria, and clinical evidence.…

cs.AI2026

Streaming Hallucination Detection in Long Chain-of-Thought Reasoning

Haolang Lu, Minghui Pan, Ripeng Li +6

Long chain-of-thought (CoT) reasoning improves the performance of large language models, yet hallucinations in such settings often emerge subtly and propagate across reasoning step…

cs.CR2025

LeechHijack: Covert Computational Resource Exploitation in Intelligent Agent Systems

Yuanhe Zhang, Weiliu Wang, Zhenhong Zhou +5

Large Language Model (LLM)-based agents have demonstrated remarkable capabilities in reasoning, planning, and tool usage. The recently proposed Model Context Protocol (MCP) has eme…

cs.CL2025

LIFEBench: Evaluating Length Instruction Following in Large Language Models

Wei Zhang, Zhenhong Zhou, Kun Wang +9

While large language models (LLMs) can solve PhD-level reasoning problems over long context inputs, they still struggle with a seemingly simpler task: following explicit length ins…

cs.AI2024★ 3 cited

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia

Miao Yu, Junyuan Mao, Guibin Zhang +7

Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world. Studies suggest th…

cs.CL2024

On the Role of Attention Heads in Large Language Model Safety

Zhenhong Zhou, Haiyang Yu, Xinghua Zhang +6

Large language models (LLMs) achieve state-of-the-art performance on multiple language tasks, yet their safety guardrails can be circumvented, leading to harmful generations. In li…