21 citations · 27 across the 15 of their papers we have counts for
17 papers
Deformations of Holomorphic -Contact Structures
Dan Popovici
We investigate the notion of holomorphic -contact structure, that we introduced recently in the scalar case with H. Kasuya and L. Ugarte and in the line-bundle case with K. Brod…
SearchJev: A Calibrated System-1 Model for Search Agents
Congfeng Cao, Lipeng Zuo, Konstantinos Papakostas +7
Search agents repeatedly make short decisions about relevance, evidence sufficiency, and search actions. Using generative language models for these decisions introduces latency and…
RubricReviewer: From Direct Critique to Objective and Comprehensive Rubric-Driven Peer Review
Shuyu Guo, Wenxiang Hu, Yuyue Zhao +2
Peer review at major venues is under unprecedented submission pressure, motivating the use of large language models (LLMs) as review assistants. Existing LLM-based reviewers, howev…
EvoIdeator: Evolving Scientific Ideas through Checklist-Grounded Reinforcement Learning
Andreas Sauter, Yuyue Zhao, Jacopo Urbani +5
Scientific idea generation is a cornerstone of autonomous knowledge discovery, yet the iterative evolution required to transform initial concepts into high-quality research proposa…
EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery
Yougang Lyu, Xi Zhang, Xinhao Yi +11
The increasing adoption of Large Language Models (LLMs) has enabled AI scientists to perform complex end-to-end scientific discovery tasks requiring coordination of specialized rol…
Deep Research: A Systematic Survey
Zhengliang Shi, Yiqun Chen, Haitao Li +23
Large language models (LLMs) have rapidly evolved from text generators into powerful problem solvers. Yet, many open tasks demand critical thinking, multi-source, and verifiable ou…
DeepShop: A Benchmark for Deep Research Shopping Agents
Yougang Lyu, Xiaoyu Zhang, Lingyong Yan +3
Web agents for online shopping have shown great promise in automating user interactions across e-commerce platforms. Benchmarks for assessing such agents do not reflect the complex…
Self-Adaptive Cognitive Debiasing for Large Language Models in Decision-Making
Yougang Lyu, Shijie Ren, Yue Feng +4
Large language models (LLMs) have shown potential in supporting decision-making applications, particularly as personal assistants in the financial, healthcare, and legal domains. W…
Agent-centric Information Access
Evangelos Kanoulas, Panagiotis Eustratiadis, Yongkang Li +5
As large language models (LLMs) become more specialized, we envision a future where millions of expert LLMs exist, each trained on proprietary data and excelling in specific domain…
A Cooperative Multi-Agent Framework for Zero-Shot Named Entity Recognition
Zihan Wang, Ziqi Zhao, Yougang Lyu +3
Zero-shot named entity recognition (NER) aims to develop entity recognition systems from unannotated text corpora. This task presents substantial challenges due to minimal human in…
The 1st Workshop on Human-Centered Recommender Systems
Kaike Zhang, Yunfan Wu, Yougang lyu +6
Recommender systems are quintessential applications of human-computer interaction. Widely utilized in daily life, they offer significant convenience but also present numerous chall…
Cognitive Biases in Large Language Models for News Recommendation
Yougang Lyu, Xiaoyu Zhang, Zhaochun Ren +1
Despite large language models (LLMs) increasingly becoming important components of news recommender systems, employing LLMs in such systems introduces new risks, such as the influe…
MACPO: Weak-to-Strong Alignment via Multi-Agent Contrastive Preference Optimization
Yougang Lyu, Lingyong Yan, Zihan Wang +4
As large language models (LLMs) are rapidly advancing and achieving near-human capabilities on specific tasks, aligning them with human values is becoming more urgent. In scenarios…
Towards Empathetic Conversational Recommender Systems
Xiaoyu Zhang, Ruobing Xie, Yougang Lyu +7
Conversational recommender systems (CRSs) are able to elicit user preferences through multi-turn dialogues. They typically incorporate external knowledge and pre-trained language m…
KnowTuning: Knowledge-aware Fine-tuning for Large Language Models
Yougang Lyu, Lingyong Yan, Shuaiqiang Wang +6
Despite their success at many natural language processing (NLP) tasks, large language models still struggle to effectively leverage knowledge for knowledge-intensive tasks, manifes…
Multi-Defendant Legal Judgment Prediction via Hierarchical Reasoning
Yougang Lyu, Jitai Hao, Zihan Wang +6
Multiple defendants in a criminal fact description generally exhibit complex interactions, and cannot be well handled by existing Legal Judgment Prediction (LJP) methods which focu…
Feature-Level Debiased Natural Language Understanding
Yougang Lyu, Piji Li, Yechang Yang +5
Natural language understanding (NLU) models often rely on dataset biases rather than intended task-relevant features to achieve high performance on specific datasets. As a result,…