3 citations · 3 across the 7 of their papers we have counts for
7 papers
Context Tokens are Anchors: Understanding the Repetition Curse in dMLLMs from an Information Flow Perspective
Qiyan Zhao, Xiaofeng Zhang, Shuochen Chang +7
Recent diffusion-based Multimodal Large Language Models (dMLLMs) suffer from high inference latency and therefore rely on caching techniques to accelerate decoding. However, the ap…
Hallucination Begins Where Saliency Drops
Xiaofeng Zhang, Yuanchao Zhu, Chaochen Gu +8
Recent studies have examined attention dynamics in large vision-language models (LVLMs) to detect hallucinations. However, existing approaches remain limited in reliably distinguis…
SalaMAnder: Shapley-based Mathematical Expression Attribution and Metric for Chain-of-Thought Reasoning
Yue Xin, Chen Shen, Shaotian Yan +5
Chain-of-Thought (CoT) prompting enhances the math reasoning capability of large language models (LLMs) to a large margin. However, the mechanism underlying such improvements remai…
MCA-LLaVA: Manhattan Causal Attention for Reducing Hallucination in Large Vision-Language Models
Qiyan Zhao, Xiaofeng Zhang, Yiheng Li +7
Hallucinations pose a significant challenge in Large Vision Language Models (LVLMs), with misalignment between multimodal features identified as a key contributing factor. This pap…
Efficient Reasoning Through Suppression of Self-Affirmation Reflections in Large Reasoning Models
Kaiyuan Liu, Chen Shen, Zhanwei Zhang +3
While recent advances in large reasoning models have demonstrated remarkable performance, efficient reasoning remains critical due to the rapid growth of output length. Existing op…
Improving Complex Reasoning with Dynamic Prompt Corruption: A soft prompt Optimization Approach
Sinan Fan, Liang Xie, Chen Shen +7
Prompt-tuning (PT) for large language models (LLMs) can facilitate the performance on various conventional NLP tasks with significantly fewer trainable parameters. However, our inv…