6 citations · 11 across the 25 of their papers we have counts for
28 papers
LegalWorld: A Life-Cycle Interactive Environment for Legal Agents
Songhan Zuo, Shengbin Yue, Tao Chiang +4
Civil litigation is inherently a life-cycle process: what a lawyer drafts on day one constrains what unfolds at trial months later. Yet existing legal benchmarks evaluate isolated…
From Knowing to Acting: Benchmarking Self-Awareness Capability of LLM Agents
Yifan Li, Shengbin Yue, Boyu Feng +6
The integration of external tools has transitioned LLM agents from passive responders to autonomous systems. However, current benchmarks prioritize execution success, neglecting se…
HyLaT: Efficient Multi-Agent Communication via Hybrid Latent-Text Protocol
Xinyi Mou, Siyuan Wang, Zejun Li +2
Communication protocol design is a central challenge in large language model-based multi-agent systems. Existing single-channel approaches face an inherent communication trilemma:…
ACE: Self-Evolving LLM Coding Framework via Adversarial Unit Test Generation and Preference Optimization
Yixu Huang, Xinglei Yu, Zhongyu Wei
Large Language Models (LLMs) excel at code generation but remain heavily reliant on large-scale annotated solutions and verification-based supervision, which constrains scalability…
StreamProfileBench: A Benchmark for Fine-Grained User Profile Inference in Real-World Streaming Scenarios
Sizhe Wang, Feiyu Duan, Juelin Wang +2
Large Language Models (LLMs) have reshaped user profiling, yet current evaluations mainly focus on static data snapshots. This paradigm overlooks the reality of personalized system…
Rethinking the Efficiency and Effectiveness of Reinforcement Learning for Radiology Report Generation
Zilin Lu, Ruifeng Yuan, Weiwei Cao +6
Radiologists highly desire fully automated AI for radiology report generation (R2G), yet existing approaches fall short in clinical utility. Reinforcement learning (RL) holds poten…
UniReason 1.0: A Unified Reasoning Framework for World Knowledge Aligned Image Generation and Editing
Dianyi Wang, Chaofan Ma, Feng Han +8
Unified multimodal models often struggle with complex synthesis tasks that demand deep reasoning, and typically treat text-to-image generation and image editing as isolated capabil…
DeepGen 1.0: A Lightweight Unified Multimodal Model for Advancing Image Generation and Editing
Dianyi Wang, Ruihang Li, Feng Han +17
Current unified multimodal models for image generation and editing typically rely on massive parameter scales (e.g., >10B), entailing prohibitive training costs and deployment foot…
MAGNET: Towards Adaptive GUI Agents with Memory-Driven Knowledge Evolution
Libo Sun, Jiwen Zhang, Siyuan Wang +1
Mobile GUI agents powered by large foundation models enable autonomous task execution, but frequent updates altering UI appearance and reorganizing workflows cause agents trained o…
Interleaved Latent Visual Reasoning with Selective Perceptual Modeling
Shuai Dong, Siyuan Wang, Xingyu Liu +3
Interleaved reasoning paradigms enhance Multimodal Large Language Models (MLLMs) with visual feedback but are hindered by the prohibitive computational cost of re-encoding pixel-de…
HardcoreLogic: Challenging Large Reasoning Models with Long-tail Logic Puzzle Games
Jingcong Liang, Shijun Wan, Xuehai Wu +5
Large Reasoning Models (LRMs) have demonstrated impressive performance on complex tasks, including logical puzzle games that require deriving solutions satisfying all constraints.…
FinTeam: A Multi-Agent Collaborative Intelligence System for Comprehensive Financial Scenarios
Yingqian Wu, Qiushi Wang, Zefei Long +7
Financial report generation tasks range from macro- to micro-economics analysis, also requiring extensive data analysis. Existing LLM models are usually fine-tuned on simple QA tas…
Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments
Zheng Jia, Shengbin Yue, Wei Chen +5
The gap between static benchmarks and the dynamic nature of real-world legal practice poses a key barrier to advancing legal intelligence. To this end, we introduce J1-ENVS, the fi…
Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better
Dianyi Wang, Wei Song, Yikun Wang +4
Typical large vision-language models (LVLMs) apply autoregressive supervision solely to textual sequences, without fully incorporating the visual modality into the learning process…
Not All Models Suit Expert Offloading: On Local Routing Consistency of Mixture-of-Expert Models
Jingcong Liang, Siyuan Wang, Miren Tian +3
Mixture-of-Experts (MoE) enables efficient scaling of large language models (LLMs) with sparsely activated experts during inference. To effectively deploy large MoE models on memor…
OViP: Online Vision-Language Preference Learning for VLM Hallucination
Shujun Liu, Siyuan Wang, Zejun Li +3
Large vision-language models (LVLMs) remain vulnerable to hallucination, often generating content misaligned with visual inputs. Although recent training-based approaches aim to mi…
How Jailbreak Defenses Work and Ensemble? A Mechanistic Investigation
Zhuohang Long, Siyuan Wang, Shujun Liu +3
Jailbreak attacks, where harmful prompts bypass generative models' built-in safety, raise serious concerns about model vulnerability. While many defense methods have been proposed,…
Multi-Agent Simulator Drives Language Models for Legal Intensive Interaction
Shengbin Yue, Ting Huang, Zheng Jia +5
Large Language Models (LLMs) have significantly advanced legal intelligence, but the scarcity of scenario data impedes the progress toward interactive legal scenarios. This paper i…
Stepwise Informativeness Search for Efficient and Effective LLM Reasoning
Siyuan Wang, Enda Zhao, Zhongyu Wei +1
Advances in Large Language Models (LLMs) have significantly improved multi-step reasoning through generating free-text rationales. However, recent studies show that LLMs tend to lo…
InsQABench: Benchmarking Chinese Insurance Domain Question Answering with Large Language Models
Jing Ding, Kai Feng, Binbin Lin +6
The application of large language models (LLMs) has achieved remarkable success in various fields, but their effectiveness in specialized domains like the Chinese insurance industr…
MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration
Lai Wei, Wenkai Wang, Xiaoyu Shen +5
In recent advancements, multimodal large language models (MLLMs) have been fine-tuned on specific medical image datasets to address medical visual question answering (Med-VQA) task…
Symbolic Working Memory Enhances Language Models for Complex Rule Application
Siyuan Wang, Zhongyu Wei, Yejin Choi +1
Large Language Models (LLMs) have shown remarkable reasoning performance but struggle with multi-step deductive reasoning involving a series of rule application steps, especially w…
Fine-Tuned Large Language Model for Visualization System: A Study on Self-Regulated Learning in Education
Lin Gao, Jing Lu, Zekai Shao +7
Large Language Models (LLMs) have shown great potential in intelligent visualization systems, especially for domain-specific applications. Integrating LLMs into visualization syste…
Identity-Driven Hierarchical Role-Playing Agents
Libo Sun, Siyuan Wang, Xuanjing Huang +1
Utilizing large language models (LLMs) to achieve role-playing has gained great attention recently. The primary implementation methods include leveraging refined prompts and fine-t…