6 citations · 40 across the 46 of their papers we have counts for
49 papers
PhysEvo: Astra Can Act, Let It
Wenqing Tian, Zeyu Zhang, Zhaocheng Liu +3
Astra can act, yet reliable manipulation depends on the system through which it observes and controls the world. We introduce PhysEvo, a framework for physical recursive self-impro…
EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents
Jianan Xie, Xin Sun, Zhongqi Chen +4
Outcome-based reinforcement learning enables search-augmented language agents to learn from verifiable final answers, but its trajectory-level credit cannot distinguish the contrib…
CRANE: Knowledge Editing for Reasoning MLLMs
Han Huang, Hao Wang, Mengqi Zhang +3
The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers, has introduced a new challen…
Learning When Not to Act: Mitigating Tool Abuse in Agentic Reinforcement Learning
Liuji Chen, Dianxing Tang, Xing Shi +4
Agentic reinforcement learning can induce tool abuse, where models overuse external tools even for queries solvable by internal reasoning. Existing approaches mitigate this issue w…
From Profiles to Steering Vectors: Global Sparse Priors and Local Semantic Calibration for Personalized Text Generation
Liuji Chen, Zeyu Zhang, Xinyuan Zhang +4
Personalized text generation requires models to capture user-specific writing styles from historical data. Existing approaches based on retrieval, parameter-efficient fine-tuning,…
MultiBind: A Benchmark for Attribute Misbinding in Multi-Subject Generation
Wenqing Tian, Hanyi Mao, Zhaocheng Liu +4
Subject-driven image generation is increasingly expected to support fine-grained control over multiple entities within a single image. In multi-reference workflows, users may provi…
Chatting with Images for Introspective Visual Thinking
Junfei Wu, Jian Guan, Qiang Liu +4
Current large vision-language models (LVLMs) typically rely on text-only reasoning based on a single-pass visual encoding, which often leads to loss of fine-grained visual informat…
NAG: A Unified Native Architecture for Encoder-free Text-Graph Modeling in Language Models
Haisong Gong, Zhibo Liu, Qiang Liu +2
Prevailing methods for integrating graphs into Language Models (LMs) typically rely on a segregated architecture: external Graph Neural Networks (GNNs) encode structural topology,…
ToolWeaver: Weaving Collaborative Semantics for Scalable Tool Use in Large Language Models
Bowen Fang, Wen Ye, Yunyue Su +8
Prevalent retrieval-based tool-use pipelines struggle with a dual semantic challenge: their retrievers often employ encoders that fail to capture complex semantics, while the Large…
Predict the Retrieval! Test time adaptation for Retrieval Augmented Generation
Xin Sun, Zhongqi Chen, Qiang Liu +5
Retrieval-Augmented Generation (RAG) has emerged as a powerful approach for enhancing large language models' question-answering capabilities through the integration of external kno…
KBQA-R1: Reinforcing Large Language Models for Knowledge Base Question Answering
Xin Sun, Zhongqi Chen, Xing Zheng +6
Knowledge Base Question Answering (KBQA) challenges models to bridge the gap between natural language and strict knowledge graph schemas by generating executable logical forms. Whi…
AgriDoctor: A Multimodal Intelligent Assistant for Agriculture
Mingqing Zhang, Zhuoning Xu, Peijie Wang +6
Accurate crop disease diagnosis is essential for sustainable agriculture and global food security. Existing methods, which primarily rely on unimodal models such as image-based cla…
Mining the Social Fabric: Unveiling Communities for Fake News Detection in Short Videos
Haisong Gong, Bolan Su, Xinrong Zhang +4
Short video platforms have become a major medium for information sharing, but their rapid content generation and algorithmic amplification also enable the widespread dissemination…
SpectraLLM: Uncovering the Ability of LLMs for Molecular Structure Elucidation from Multi-Spectral Data
Yunyue Su, Jiahui Chen, Zao Jiang +4
Automated molecular structure elucidation remains challenging, as existing approaches often depend on pre-compiled databases or restrict themselves to single spectroscopic modaliti…
DiffSpectra: Molecular Structure Elucidation from Spectra using Diffusion Models
Liang Wang, Yu Rong, Tingyang Xu +7
Molecular structure elucidation from spectra is a fundamental challenge in molecular science. Conventional approaches rely heavily on expert interpretation and lack scalability, wh…
Divide-Then-Align: Honest Alignment based on the Knowledge Boundary of RAG
Xin Sun, Jianan Xie, Zhongqi Chen +7
Large language models (LLMs) augmented with retrieval systems have significantly advanced natural language processing tasks by integrating external knowledge sources, enabling more…
REACT: Representation Extraction And Controllable Tuning to Overcome Overfitting in LLM Knowledge Editing
Haitian Zhong, Yuhuan Liu, Ziyang Xu +6
Large language model editing methods frequently suffer from overfitting, wherein factual updates can propagate beyond their intended scope, overemphasizing the edited target even w…
Graffe: Graph Representation Learning via Diffusion Probabilistic Models
Dingshuo Chen, Shuchen Xue, Liuji Chen +5
Diffusion probabilistic models (DPMs), widely recognized for their potential to generate high-quality samples, tend to go unnoticed in representation learning. While recent progres…
Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation
Liuji Chen, Xiaofang Yang, Yuanzhuo Lu +6
Retrieval-Augmented Generation (RAG) systems improve the factual grounding of large language models (LLMs) but remain vulnerable to retrieval poisoning, where adversaries seed the…
SINCon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection
Mingqing Zhang, Qiang Liu, Xiang Tao +2
In the era of rapidly evolving large language models (LLMs), state-of-the-art rumor detection systems, particularly those based on Message Propagation Trees (MPTs), which represent…
SEEM: Exploiting Black-Box Text Attacks to Manipulate Tool Selection
Liuji Chen, Hao Gao, Jinghao Zhang +3
Tool learning has emerged as a powerful auxiliary mechanism that extends the capabilities of large language models (LLMs), enabling them to address complex tasks that demand real-t…
Personalized Text Generation with Contrastive Activation Steering
Jinghao Zhang, Yuting Liu, Wenjie Wang +4
Personalized text generation aims to infer users' writing style preferences from their historical texts and generate outputs that faithfully reflect these stylistic characteristics…
MolSpectra: Pre-training 3D Molecular Representation with Multi-modal Energy Spectra
Liang Wang, Shaozhen Liu, Yu Rong +3
Establishing the relationship between 3D structures and the energy states of molecular systems has proven to be a promising approach for learning 3D molecular representations. Howe…
Diffusion Models for Molecules: A Survey of Methods and Tasks
Liang Wang, Chao Song, Zhiyuan Liu +3
Generative tasks about molecules, including but not limited to molecule generation, are crucial for drug discovery and material design, and have consistently attracted significant…