2 citations · 3 across the 12 of their papers we have counts for
12 papers
Token-level Data Selection for Safe LLM Fine-tuning
Yanping Li, Zhening Liu, Zijian Li +2
Fine-tuning large language models (LLMs) on custom datasets has become a standard approach for adapting these models to specific domains and applications. However, recent studies h…
WirelessAgent++: Automated Agentic Workflow Design and Benchmarking for Wireless Networks
Jingwen Tong, Zijian Li, Fang Liu +2
The integration of large language models (LLMs) into wireless networks has sparked growing interest in building autonomous AI agents for wireless tasks. However, existing approache…
Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning
Xin Guan, Zijian Li, Shen Huang +3
While Reinforcement Learning (RL) has advanced LLM reasoning, applying it to long-context scenarios is hindered by sparsity of outcome rewards. This limitation fails to penalize un…
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…
RemedyGS: Defend 3D Gaussian Splatting against Computation Cost Attacks
Yanping Li, Zhening Liu, Zijian Li +2
As a mainstream technique for 3D reconstruction, 3D Gaussian splatting (3DGS) has been applied in a wide range of applications and services. Recent studies have revealed critical v…
Hierarchical Dual-Strategy Unlearning for Biomedical and Healthcare Intelligence Using Imperfect and Privacy-Sensitive Medical Data
Yi Zhang, Chao Zhang, Zijian Li +7
Large language models (LLMs) exhibit exceptional performance but pose substantial privacy risks due to training data memorization, particularly within healthcare contexts involving…
WebWeaver: Structuring Web-Scale Evidence with Dynamic Outlines for Open-Ended Deep Research
Zijian Li, Xin Guan, Bo Zhang +9
This paper tackles \textbf{open-ended deep research (OEDR)}, a complex challenge where AI agents must synthesize vast web-scale information into insightful reports. Current approac…
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.…
Learn as Individuals, Evolve as a Team: Multi-agent LLMs Adaptation in Embodied Environments
Xinran Li, Chenjia Bai, Zijian Li +3
Large language models (LLMs) possess extensive knowledge bases and strong reasoning capabilities, making them promising tools for complex, multi-agent planning in embodied environm…
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…
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…
Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients
Xiaolu Wang, Zijian Li, Shi Jin +1
Federated learning (FL) is an emerging distributed training paradigm that aims to learn a common global model without exchanging or transferring the data that are stored locally at…