25 citations · 54 across the 28 of their papers we have counts for
6 papers · 1 filter
Is Multimodal Speculative Decoding Ready for Diffusion-Based Parallel Drafting? A Survey and Empirical Diagnosis
Yantao Li, Huanlin Gao, Fang Zhao +12
Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them in parallel. Its lossless g…
Recognize Your Orchestrator: An Entropy Dynamics Perspective for LLM Multi-Agent Systems
Junze Zhu, Weihao Chen, Xuanwang Zhang +2
The transition from single-turn models to Multi-Agent Systems (MAS) promises enhanced problem-solving capabilities, yet the centralized orchestration topology remains a critical po…
Causal Evidence for Attention Head Imbalance in Modality Conflict Hallucination
Jinrui Jiang, Zhangtai Wu, Zhen Wu +1
Modality-conflict hallucination occurs when multimodal large language models (MLLMs) prioritize erroneous textual premises over contradictory visual evidence. To understand why vis…
TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them
Yidong Wang, Yunze Song, Tingyuan Zhu +11
The adoption of Large Language Models (LLMs) as automated evaluators (LLM-as-a-judge) has revealed critical inconsistencies in current evaluation frameworks. We identify two fundam…
Neutralizing Popularity Bias in LLM-based Recommendation via Counterfactual Reasoning Guidelines
Guanrong Li, Haolin Yang, Xinyu Liu +3
In the era of generative AI, recommender systems are moving from precise prediction to trustworthy generation. Large language models (LLMs) support this shift by inferring user int…
Rethinking Relation Extraction: Beyond Shortcuts to Generalization with a Debiased Benchmark
Liang He, Yougang Chu, Zhen Wu +3
Benchmarks are crucial for evaluating machine learning algorithm performance, facilitating comparison and identifying superior solutions. However, biases within datasets can lead m…