10 papers
How Should Diffusion Language Models Edit Code?
Xijia Tao, Ziru Liu, Shansan Gong +7
Code editing requires a model to decide where to make changes, generate the new content, and preserve everything else. We study how masked diffusion language models divide these re…
VizRAG: Enhancing Retrieval-Augmented Generation with Hypergraph Visualization
Yanbin Wei, Yang Chen, Renling Gan +7
Hypergraph-based RAG systems surpass traditional graph-based approaches by organizing complex n-ary atomic facts among entities, rather than relying solely on binary relationships.…
Multi-Turn Reasoning When Context Arrives in Pieces: Scalable Sharding and Memory-Augmented RL
Shu Tong Luo, Wenqin Liu, Rui Liu +2
When a user reveals task-critical information across several conversation turns, LLM accuracy drops by up to 65% despite full context availability. We show that this Lost in Conver…
RAG-KT: Cross-platform Explainable Knowledge Tracing with Multi-view Fusion Retrieval Generation
Zhiyi Duan, Hongyu Yuan, Rui Liu
Knowledge Tracing (KT) infers a student's knowledge state from past interactions to predict future performance. Conventional Deep Learning (DL)-based KT models are typically tied t…
HyperGVL: Benchmarking and Improving Large Vision-Language Models in Hypergraph Understanding and Reasoning
Yanbin Wei, Chun Kang, Siwei Li +11
Large Vision-Language Models (LVLMs) consistently require new arenas to guide their expanding boundaries, yet their capabilities with hypergraphs remain unexplored. In the real wor…
InsEdit: Towards Instruction-based Visual Editing via Data-Efficient Video Diffusion Models Adaptation
Zhefan Rao, Bin Zou, Haoxuan Che +5
Instruction-based video editing is a natural way to control video content with text, but adapting a video generation model into an editor usually appears data-hungry. At the same t…
An AI-Based Structured Semantic Control Model for Stable and Coherent Dynamic Interactive Content Generation
Rui Liu
This study addresses the challenge that generative models struggle to balance flexibility, stability, and controllability in complex interactive scenarios. It proposes a controllab…
Compress the Easy, Explore the Hard: Difficulty-Aware Entropy Regularization for Efficient LLM Reasoning
Qin-Wen Luo, Sheng Ren, Xiang Chen +4
Chain-of-Thought (CoT) has substantially empowered Large Language Models (LLMs) to tackle complex reasoning tasks, yet the verbose nature of explicit reasoning steps incurs prohibi…
Beyond Confidence: Adaptive and Coherent Decoding for Diffusion Language Models
Kecheng Chen, Ziru Liu, Xijia Tao +7
Diffusion Language Models (DLMs) have recently achieved significant success due to their any-order generation capabilities. However, existing inference methods typically rely on lo…
MMSearch-Plus: Benchmarking Provenance-Aware Search for Multimodal Browsing Agents
Xijia Tao, Yihua Teng, Xinxing Su +7
Existing multimodal browsing benchmarks often fail to require genuine multimodal reasoning, as many tasks can be solved with text-only heuristics without vision-in-the-loop verific…