153 citations · 213 across the 39 of their papers we have counts for
15 papers · 1 filter
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…
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…
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…
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…
Latent Inter-User Difference Modeling for LLM Personalization
Yilun Qiu, Tianhao Shi, Xiaoyan Zhao +3
Large language models (LLMs) are increasingly integrated into users' daily lives, leading to a growing demand for personalized outputs. Previous work focuses on leveraging a user's…
IGD: Token Decisiveness Modeling via Information Gain in LLMs for Personalized Recommendation
Zijie Lin, Yang Zhang, Xiaoyan Zhao +3
Large Language Models (LLMs) have shown strong potential for recommendation by framing item prediction as a token-by-token language generation task. However, existing methods treat…
Optimizing Knowledge Integration in Retrieval-Augmented Generation with Self-Selection
Yan Weng, Fengbin Zhu, Tong Ye +3
Retrieval-Augmented Generation (RAG), which integrates external knowledge into Large Language Models (LLMs), has proven effective in enabling LLMs to produce more accurate and reli…
Cooperative SQL Generation for Segmented Databases By Using Multi-functional LLM Agents
Zhiguang Wu, Fengbin Zhu, Xuequn Shang +2
Text-to-SQL task aims to automatically yield SQL queries according to user text questions. To address this problem, we propose a Cooperative SQL Generation framework based on Multi…
Large Language Models Empowered Personalized Web Agents
Hongru Cai, Yongqi Li, Wenjie Wang +4
Web agents have emerged as a promising direction to automate Web task completion based on user instructions, significantly enhancing user experience. Recently, Web agents have evol…
CrAM: Credibility-Aware Attention Modification in LLMs for Combating Misinformation in RAG
Boyi Deng, Wenjie Wang, Fengbin Zhu +2
Retrieval-Augmented Generation (RAG) can alleviate hallucinations of Large Language Models (LLMs) by referencing external documents. However, the misinformation in external documen…
Think Twice Before Trusting: Self-Detection for Large Language Models through Comprehensive Answer Reflection
Moxin Li, Wenjie Wang, Fuli Feng +3
Self-detection for Large Language Models (LLMs) seeks to evaluate the trustworthiness of the LLM's output by leveraging its own capabilities, thereby alleviating the issue of outpu…
TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Data
Fengbin Zhu, Ziyang Liu, Fuli Feng +3
In this work, we address question answering (QA) over a hybrid of tabular and textual data that are very common content on the Web (e.g. SEC filings), where discrete reasoning capa…
Doc2SoarGraph: Discrete Reasoning over Visually-Rich Table-Text Documents via Semantic-Oriented Hierarchical Graphs
Fengbin Zhu, Chao Wang, Fuli Feng +3
Discrete reasoning over table-text documents (e.g., financial reports) gains increasing attention in recent two years. Existing works mostly simplify this challenge by manually sel…
TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance
Fengbin Zhu, Wenqiang Lei, Youcheng Huang +5
Hybrid data combining both tabular and textual content (e.g., financial reports) are quite pervasive in the real world. However, Question Answering (QA) over such hybrid data is la…