10 papers
Small Frequency Corrections Can Change What Survives KV Cache Compression
Hong Chen, Yudong Zeng, Yongwei Huang +5
Compressing a key-value cache before its next question is known requires choosing what to retain without knowing which evidence will matter. Value energy measures entry strength bu…
SemTrace: Source-Grounded Semantic Signatures for Tracing LLM Exposure to Protected Documents
Junyan Zhang, Yudong Zeng, Yongwei Huang +3
Large language models are increasingly used to read documents and produce downstream text, creating a provenance problem when the document owner cannot control or inspect the model…
EffiReason-Bench: A Unified Benchmark for Evaluating and Advancing Efficient Reasoning in Large Language Models
Junquan Huang, Haotian Wu, Yubo Gao +7
Large language models (LLMs) with Chain-of-Thought (CoT) prompting achieve strong reasoning but often produce unnecessarily long explanations, increasing cost and sometimes reducin…
MOSS-ChatV: Reinforcement Learning with Process Reasoning Reward for Video Temporal Reasoning
Sicheng Tao, Jungang Li, Yibo Yan +8
Video reasoning has emerged as a critical capability for multimodal large language models (MLLMs), requiring models to move beyond static perception toward coherent understanding o…
PMark: Towards Robust and Distortion-free Semantic-level Watermarking with Channel Constraints
Jiahao Huo, Shuliang Liu, Bin Wang +5
Semantic-level watermarking (SWM) for large language models (LLMs) enhances watermarking robustness against text modifications and paraphrasing attacks by treating the sentence as…
Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities
Junyan Zhang, Yubo Gao, Yibo Yan +8
The finetuning of Large Language Models (LLMs) has significantly advanced their instruction-following capabilities, yet the underlying computational mechanisms driving these improv…
Do BERT-Like Bidirectional Models Still Perform Better on Text Classification in the Era of LLMs?
Junyan Zhang, Yiming Huang, Shuliang Liu +2
The rapid adoption of LLMs has overshadowed the potential advantages of traditional BERT-like models in text classification. This study challenges the prevailing "LLM-centric" tren…
PhysicsArena: The First Multimodal Physics Reasoning Benchmark Exploring Variable, Process, and Solution Dimensions
Song Dai, Yibo Yan, Jiamin Su +8
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in diverse reasoning tasks, yet their application to complex physics reasoning remains underexplo…
RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection
Yiming Huang, Junyan Zhang, Zihao Wang +5
Large Language Models (LLMs) have become powerful, but hallucinations remain a vital obstacle to their trustworthy use. Previous works improved the capability of hallucination dete…
CoheMark: A Novel Sentence-Level Watermark for Enhanced Text Quality
Junyan Zhang, Shuliang Liu, Aiwei Liu +4
Watermarking technology is a method used to trace the usage of content generated by large language models. Sentence-level watermarking aids in preserving the semantic integrity wit…