1 citations · 1 across the 12 of their papers we have counts for
13 papers
Decoupling Knowledge Forgetting and Refusal Learning in MLLM Unlearning
Haodong Chen, Shengtao Wen, Dong Liang +2
Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information. This surface-level criterion, however, masks two critical failu…
ITER: Interaction-Aware Retrieval for Agentic Search
Haodong Chen, Shuai Wang, Yu Yin +3
Deep-research agents answer complex user questions through an iterative sequence of search steps, where the agent autonomously formulates sub-queries to retrieve the evidence neede…
Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Search Agents
Shuai Wang, Haodong Chen, Yu Yin +3
Existing deep-search agents use a Search-Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata…
Knowing but Not Saying: Preventing Factual Access Failures in LLM SFT via Recall-Anchored Distillation
Haodong Chen, Yadong Wang, Shengtao Wen +2
Supervised fine-tuning (SFT) can degrade factual behavior outside the target domain. This degradation is often described as catastrophic forgetting, yet open-ended factual failures…
X+Slides: Benchmarking Audience-Conditioned Slide Generation
Haodong Chen, Xuanhe Zhou, Wei Zhou +6
Automatically generating slide decks from source documents is an important application of large language models (LLMs). Existing benchmarks primarily assess slide completeness and…
Beyond Dense States: Sparse Transcoders as Causally Testable Operators for LLM Latent Reasoning
Yadong Wang, Haodong Chen, Yu Tian +3
Latent reasoning reduces the token-generation cost of chain-of-thought reasoning by replacing explicit intermediate tokens with continuous latent transitions. However, existing lat…
When Abundance Conceals Weakness: Knowledge Conflict in Multilingual Models
Jiaqi Zhao, Qiang Huang, Haodong Chen +2
Large Language Models (LLMs) encode vast world knowledge across multiple languages, yet their internal beliefs are often unevenly distributed across linguistic spaces. When externa…
Measuring Social Bias in Vision-Language Models with Face-Only Counterfactuals from Real Photos
Haodong Chen, Qiang Huang, Jiaqi Zhao +3
Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demographic cues. A central challenge in me…
FineQuest: Adaptive Knowledge-Assisted Sports Video Understanding via Agent-of-Thoughts Reasoning
Haodong Chen, Haojian Huang, XinXiang Yin +1
Video Question Answering (VideoQA) based on Large Language Models (LLMs) has shown potential in general video understanding but faces significant challenges when applied to the inh…
MultiMedEdit: A Scenario-Aware Benchmark for Evaluating Knowledge Editing in Medical VQA
Shengtao Wen, Haodong Chen, Yadong Wang +6
Knowledge editing (KE) provides a scalable approach for updating factual knowledge in large language models without full retraining. While previous studies have demonstrated effect…
A Survey of LLM DATA
Xuanhe Zhou, Junxuan He, Wei Zhou +14
The integration of large language model (LLM) and data management (DATA) is rapidly redefining both domains. In this survey, we comprehensively review the bidirectional relationshi…
VistaDPO: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models
Haojian Huang, Haodong Chen, Shengqiong Wu +5
Large Video Models (LVMs) built upon Large Language Models (LLMs) have shown promise in video understanding but often suffer from misalignment with human intuition and video halluc…
SeFAR: Semi-supervised Fine-grained Action Recognition with Temporal Perturbation and Learning Stabilization
Yongle Huang, Haodong Chen, Zhenbang Xu +3
Human action understanding is crucial for the advancement of multimodal systems. While recent developments, driven by powerful large language models (LLMs), aim to be general enoug…