153 citations · 213 across the 39 of their papers we have counts for
44 papers
FinNextAssist: Towards Professional Financial Deep Research Assistant
Xiangyu Li, Fengbin Zhu, Xuan Yao +9
Deep Research (DR) agents have demonstrated strong capabilities in complex, research-oriented tasks through autonomous planning, iterative retrieval, multi-step reasoning, and stru…
Trading Strategy Optimization via Textual Gradient
Chaoqun Yang, Qian Wang, Fengbin Zhu +4
Quantitative trading strategy design aims to discover trading programs from historical data that remain effective in future markets, which can be viewed as a black-box program opti…
ResComEmb: Effective and Efficient Multimodal Embedding via Residual Homogeneity Compression
Zijing Cai, Yuzhe Wang, Jingxian Zhu +2
Multimodal large language models (MLLMs) have shown strong potential for universal multimodal representation learning. However, existing methods either compress each input into a s…
PAWS: Policy-driven Agentic World Simulation
Tiviatis Sim, Jia Hui Woon, Xinming Gao +5
Policy interventions propagate through public communication, institutional decisions, and stakeholder responses, yet datasets for financial multi-agent simulation rarely connect th…
GenRubric: Self-Evolving Rubric Generation for Scalable LLM Evaluation
Yifan Chen, Haitao Li, Qingyao Ai +4
Large language models are increasingly used as scalable evaluators for open-ended tasks. However, many LLM judges derive query-specific criteria during scoring, leaving the evaluat…
Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents
Qi Liu, Yiqun Chen, Zidan Chen +6
Search agents now answer questions that take dozens of searches to settle, yet how such an agent reads a page has drawn far less attention than how it finds one. Nearly all of them…
Diagnosing Search Behavior and Failure Modes in Long-Horizon Search Agents
Qi Liu, Jiaxin Mao, Fengbin Zhu +1
Deep search agents answer difficult information-seeking questions by iteratively issuing search queries to gather supporting evidence, but it remains unclear whether and how greate…
FinDeepIndicator: Benchmarking Deep Research Agents in End-to-End Financial Indicator Construction
Chaoqun Yang, Fengbin Zhu, Xinyu Lin +5
Financial indicators are essential tools for transforming raw financial data into interpretable measures for various downstream tasks, such as valuation, risk assessment, and econo…
Herculean: An Agentic Benchmark for Financial Intelligence
Xueqing Peng, Zhuohan Xie, Yupeng Cao +60
As AI agents advance, the central question is no longer whether they can solve isolated financial tasks, but whether their capabilities generalize across complete professional work…
Plant, Persist, Trigger: Sleeper Attack on Large Language Model Agents
Yongxiang Li, Moxin Li, Zhixin Ma +4
Large Language Model (LLM) agents remain vulnerable to safety threats from the external environment, where attackers inject adversarial content into external observations such as t…
Scale over Preference: The Impact of AI-Generated Content on Online Content Ecology
Tianhao Shi, Yang Zhang, Xiaoyan Zhao +8
The rapid proliferation of Artificial Intelligence-Generated Content (AIGC) is fundamentally restructuring online content ecologies, necessitating a rigorous examination of its beh…
CAPSUL: A Comprehensive Human Protein Benchmark for Subcellular Localization
Yicheng Hu, Xinyu Lin, Shulin Li +3
Subcellular localization is a crucial biological task for drug target identification and function annotation. Although it has been biologically realized that subcellular localizati…
MURE: Hierarchical Multi-Resolution Encoding via Vision-Language Models for Visual Document Retrieval
Fengbin Zhu, Zijing Cai, Yuzhe Wang +5
Visual Document Retrieval (VDR) requires representations that capture both fine-grained visual details and global document structure to ensure retrieval efficacy while maintaining…
DiffuRank: Effective Document Reranking with Diffusion Language Models
Qi Liu, Kun Ai, Jiaxin Mao +6
Recent advances in large language models (LLMs) have inspired new paradigms for document reranking. While this paradigm better exploits the reasoning and contextual understanding c…
SafeNeuron: Neuron-Level Safety Alignment for Large Language Models
Zhaoxin Wang, Jiaming Liang, Fengbin Zhu +5
Large language models (LLMs) and multimodal LLMs are typically safety-aligned before release to prevent harmful content generation. However, recent studies show that safety behavio…
MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
Lin Wang, Yang Zhang, Jingfan Chen +4
The integration of reinforcement learning (RL) into large language models (LLMs) has opened new opportunities for recommender systems by eliciting reasoning and improving user pref…
Controllable Value Alignment in Large Language Models through Neuron-Level Editing
Yonghui Yang, Yihui Wang, Junwei Li +6
Aligning large language models (LLMs) with human values has become increasingly important as their influence on human behavior and decision-making expands. However, existing steeri…
PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models
Chengbing Wang, Wuqiang Zheng, Yang Zhang +5
Large Language Models (LLMs) are increasingly deployed in human-centric applications, yet they often fail to provide substantive emotional support. While Reinforcement Learning (RL…
FinDeepForecast: A Live Multi-Agent System for Benchmarking Deep Research Agents in Financial Forecasting
Xiangyu Li, Xuan Yao, Guohao Qi +16
Deep Research (DR) Agents powered by advanced Large Language Models (LLMs) have fundamentally shifted the paradigm for completing complex research tasks. Yet, a comprehensive and l…
One Adapts to Any: Meta Reward Modeling for Personalized LLM Alignment
Hongru Cai, Yongqi Li, Tiezheng Yu +4
Alignment of Large Language Models (LLMs) aims to align outputs with human preferences, and personalized alignment further adapts models to individual users. This relies on persona…
TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards
Xiqiao Xiong, Ouxiang Li, Zhuo Liu +5
Large language models have seen widespread adoption, yet they remain vulnerable to multi-turn jailbreak attacks, threatening their safe deployment. This has led to the task of trai…
FinDeepResearch: Evaluating Deep Research Agents in Rigorous Financial Analysis
Fengbin Zhu, Xiang Yao Ng, Ziyang Liu +19
Deep Research (DR) agents, powered by advanced Large Language Models (LLMs), have recently garnered increasing attention for their capability in conducting complex research tasks.…
Reinforced Strategy Optimization for Conversational Recommender Systems via Network-of-Experts
Xiaoyan Zhao, Ming Yan, Yang Zhang +6
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations through multi-turn natural language interactions with users. Given the strong interaction and…
Heterogeneous User Modeling for LLM-based Recommendation
Honghui Bao, Wenjie Wang, Xinyu Lin +4
Leveraging Large Language Models (LLMs) for recommendation has demonstrated notable success in various domains, showcasing their potential for open-domain recommendation. A key cha…