collaborators

11 papers

cs.LG2026

REOPD: Reliability-Adaptive Reward Extrapolation for On-Policy Distillation

Yang Sun, Lichao Ma, Houyuan Qin +5

On-policy distillation (OPD) trains a student on its own trajectories under dense token-level supervision from a teacher. Reward-extrapolation methods such as ExOPD amplify the tea…

cs.IR2026

EviProp: Seeded Relevance Diffusion on Chunk-Page Graphs for Long Multimodal Document Retrieval

Hongwei Zhang, Xiaoman Wang, Zehui Ling +7

Retrieving evidence pages from visually rich long documents is a key challenge in document question answering. Existing page-level visual retrievers operate under an independent ma…

cs.CL2026

IA-RAG: Interval-Algebra-Driven Temporal Reasoning for Dynamic Knowledge Retrieval

Xiaoman Wang, Yaoze Zhang, Wenzhuo Fan +7

Retrieval-Augmented Generation (RAG) has shown strong effectiveness in grounding Large Language Models (LLMs) with external knowledge. However, existing RAG and Graph RAG framework…

cs.CV2026

Investigating Redundancy in Multimodal Large Language Models with Multiple Vision Encoders

Yizhou Wang, Song Mao, Yang Chen +8

Recent multimodal large language models (MLLMs) increasingly integrate multiple vision encoders to improve performance on various benchmarks, assuming that diverse pretraining obje…

cs.CV2025

Aligning Vision to Language: Annotation-Free Multimodal Knowledge Graph Construction for Enhanced LLMs Reasoning

Junming Liu, Siyuan Meng, Yanting Gao +7

Multimodal reasoning in Large Language Models (LLMs) struggles with incomplete knowledge and hallucination artifacts, challenges that textual Knowledge Graphs (KGs) only partially…

cs.AI2025

LeanRAG: Knowledge-Graph-Based Generation with Semantic Aggregation and Hierarchical Retrieval

Yaoze Zhang, Rong Wu, Pinlong Cai +5

Retrieval-Augmented Generation (RAG) plays a crucial role in grounding Large Language Models by leveraging external knowledge, whereas the effectiveness is often compromised by the…