4 citations · 4 across the 13 of their papers we have counts for
18 papers
SafeAdapt-Poker: Counterfactual Risk Calibration for Budgeted Adaptation under Opponent Shift
Miaobo Hu, Shuhao Hu, Xiaobo Guo +5
Opponent histories can mislead after behavioral shifts. SafeAdapt-Poker formulates budgeted adaptation under opponent shift as a dual-counterfactual sequential-control problem usin…
Absorbing State Phase Transitions in Multi-Agent Search
Wenwen Zheng, Yuzhe Yang, Helen Qu +2
Nontrivial dynamics can emerge in large language model (LLM)-based multi-agent systems, and preliminary evidence exists that formalisms from statistical mechanics can be effective…
MemFold: Learning Compact Soft Memory for Long-Context Personalization via On-Policy Optimization
Jingxuan Wu, Yuzhe Yang, Yiqiao Huang +6
An assistant that serves the same user over a long horizon has to answer from what that user has revealed: which preferences still hold, which were revised, and which constraints a…
HarnessVLN: Unifying Training-Free Embodied Navigation through an Agent Harness
Yang Chen, Lirong Che, Zhenyu Huang +7
Embodied navigation requires agents to ground instructions or object goals in spatial observations and translate plans into successful execution. As multimodal large language model…
CoCoBench: A Cooperative Coordination Benchmark for Embodied Multi-Agent Task Planning
Yang Chen, Ye-Xin Xie, Lirong Che +8
Agent systems powered by multimodal large language models (MLLMs) have advanced rapidly in recent years, yet existing embodied-agent benchmarks still lack fine-grained diagnostics…
WorldMemArena: Evaluating Multimodal Agent Memory Through Action-World Interaction
Chengzhi Liu, Yuzhe Yang, Sophia Xiao Pu +14
Multimodal large language models are increasingly deployed as long-horizon agents, where memory must do more than recall: it must track an evolving world, revise what has gone stal…
Auditing Agent Harness Safety
Chengzhi Liu, Yichen Guo, Yepeng Liu +8
LLM agents increasingly run inside execution harnesses that dispatch tools, allocate resources, and route messages between specialized components. However, a harness can return a c…
Diversity Collapse in Multi-Agent LLM Systems: Structural Coupling and Collective Failure in Open-Ended Idea Generation
Nuo Chen, Yicheng Tong, Yuzhe Yang +5
Multi-agent systems (MAS) are increasingly used for open-ended idea generation, driven by the expectation that collective interaction will broaden the exploration diversity. Howeve…
MANSION: Multi-floor lANguage-to-3D Scene generatIOn for loNg-horizon tasks
Lirong Che, Shuo Wen, Shan Huang +5
Real-world robotic tasks are long-horizon and often span multiple floors, demanding rich spatial reasoning. However, existing embodied benchmarks are largely confined to single-flo…
Denoising Time Matters:Diverse Generation in Diffusion Language Models
Jingxuan Wu, Zhenglin Wan, Xingrui Yu +5
Diffusion language models (Diffusion-LMs) generate text through iterative denoising, exposing a temporal structure that is largely absent from autoregressive decoding. In this pape…
Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space
Chengzhi Liu, Yuzhe Yang, Yue Fan +3
Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced cross-modal understanding and reasoning by incorporating Chain-of-Thought (CoT) reasonin…
Presenting a Paper is an Art: Self-Improvement Aesthetic Agents for Academic Presentations
Chengzhi Liu, Yuzhe Yang, Kaiwen Zhou +5
The promotion of academic papers has become an important means of enhancing research visibility. However, existing automated methods struggle limited storytelling, insufficient aes…
Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
Jingxuan Wu, Zhenglin Wan, Xingrui Yu +4
Flow-based text-to-image models follow deterministic trajectories, making it costly to explore diverse modes under limited sampling budgets. Existing approaches to improving divers…
Feature Extraction and Steering for Enhanced Chain-of-Thought Reasoning in Language Models
Zihao Li, Xu Wang, Yuzhe Yang +3
Large Language Models (LLMs) demonstrate the ability to solve reasoning and mathematical problems using the Chain-of-Thought (CoT) technique. Expanding CoT length, as seen in model…
TwinMarket: A Scalable Behavioral and Social Simulation for Financial Markets
Yuzhe Yang, Yifei Zhang, Minghao Wu +5
The study of social emergence has long been a central focus in social science. Traditional modeling approaches, such as rule-based Agent-Based Models (ABMs), struggle to capture th…
FedDTPT: Federated Discrete and Transferable Prompt Tuning for Black-Box Large Language Models
Jiaqi Wu, Simin Chen, Yuzhe Yang +6
In recent years, large language models (LLMs) have significantly advanced the field of natural language processing (NLP). By fine-tuning LLMs with data from specific scenarios, the…
UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models
Yuzhe Yang, Yifei Zhang, Yan Hu +10
This paper introduces the UCFE: User-Centric Financial Expertise benchmark, an innovative framework designed to evaluate the ability of large language models (LLMs) to handle compl…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…