2 citations · 3 across the 13 of their papers we have counts for
13 papers
PBSD: Privileged Bayesian Self-Distillation for Long-Horizon Credit Assignment
Yang Tian, Rui Wang, Xumeng Wen +5
Long-horizon agentic tasks pose a fundamental credit assignment challenge for outcome-base reinforcement learning: trajectory-level rewards verify final correctness but provide lim…
GEAR: Granularity-Adaptive Advantage Reweighting for LLM Agents via Self-Distillation
Sijia Li, Yuchen Huang, Zifan Liu +7
Reinforcement learning has become a widely used post-training approach for LLM agents, where training commonly relies on outcome-level rewards that provide only coarse supervision.…
What to Ignore, What to React: Visually Robust RL Fine-Tuning of VLA Models
Yuanfang Peng, Jingjing Fu, Chuheng Zhang +6
Reinforcement learning (RL) fine-tuning has shown promise for Vision-Language-Action (VLA) models in robotic manipulation, but deployment-time visual shifts pose practical challeng…
Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models
Ming Sun, Rui Wang, Xingrui Yu +5
Vision-Language-Action models (VLAs) support generalist robotic control by enabling end-to-end decision policies directly from multi-modal inputs. As trained VLAs are increasingly…
3DMedAgent: Unified Perception-to-Understanding for 3D Medical Analysis
Ziyue Wang, Linghan Cai, Chang Han Low +8
3D CT analysis spans a continuum from low-level perception to high-level clinical understanding. Existing 3D-oriented analysis methods adopt either isolated task-specific modeling…
MedFeat: Model-Aware and Explainability-Driven Feature Engineering with LLMs for Tabular Prediction
Zizheng Zhang, Yiming Li, Justin Xu +6
In clinical tabular prediction, classical machine learning models with feature engineering often outperform neural methods. LLMs are increasingly used to automate this process, act…
See Less, See Right: Bi-directional Perceptual Shaping For Multimodal Reasoning
Shuoshuo Zhang, Yizhen Zhang, Jingjing Fu +4
Large vision-language models (VLMs) often benefit from intermediate visual cues, either injected via external tools or generated as latent visual tokens during reasoning, but these…
Experience-Evolving Multi-Turn Tool-Use Agent with Hybrid Episodic-Procedural Memory
Sijia Li, Yuchen Huang, Zifan Liu +6
As intents unfold and environments change, multi-turn agents face continuously shifting decision contexts. Although reusing past experience is intuitively appealing, existing appro…
PixelCraft: A Multi-Agent System for High-Fidelity Visual Reasoning on Structured Images
Shuoshuo Zhang, Zijian Li, Yizhen Zhang +6
Structured images (e.g., charts and geometric diagrams) remain challenging for multimodal large language models (MLLMs), as perceptual slips can cascade into erroneous conclusions.…
OMGM: Orchestrate Multiple Granularities and Modalities for Efficient Multimodal Retrieval
Wei Yang, Jingjing Fu, Rui Wang +3
Vision-language retrieval-augmented generation (RAG) has become an effective approach for tackling Knowledge-Based Visual Question Answering (KB-VQA), which requires external knowl…
Chain of Functions: A Programmatic Pipeline for Fine-Grained Chart Reasoning Data
Zijian Li, Jingjing Fu, Lei Song +3
Visual reasoning is crucial for multimodal large language models (MLLMs) to address complex chart queries, yet high-quality rationale data remains scarce. Existing methods leverage…
PIKE-RAG: sPecIalized KnowledgE and Rationale Augmented Generation
Jinyu Wang, Jingjing Fu, Rui Wang +2
Despite notable advancements in Retrieval-Augmented Generation (RAG) systems that expand large language model (LLM) capabilities through external retrieval, these systems often str…
Graph Neural Network Enhanced Retrieval for Question Answering of LLMs
Zijian Li, Qingyan Guo, Jiawei Shao +4
Retrieval augmented generation has revolutionized large language model (LLM) outputs by providing factual supports. Nevertheless, it struggles to capture all the necessary knowledg…