23 citations · 67 across the 14 of their papers we have counts for
14 papers
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +378
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
A governance horizon for ethical-use constraints in open-weight AI models
Weiwei Xu, Hengzhi Ye, Haoran Ye +3
Ethical constraints on open-weight AI models are both a reflection of societal concerns and a foundation for AI governance policy. They are expected to propagate to downstream deri…
Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values
Haonan Dong, Qiguan Feng, Kehan Jiang +3
Autonomous agents have rapidly matured as task executors and seen widespread deployment via harnesses such as OpenClaw. Safety concerns have rightly drawn growing research attentio…
NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons
Haonan Dong, Kehan Jiang, Haoran Ye +3
Large Reasoning Models (LRMs) have recently achieved remarkable success in complex reasoning tasks. However, closer scrutiny reveals persistent failure modes compromising performan…
VRPAgent: LLM-Driven Discovery of Heuristic Operators for Vehicle Routing Problems
André Hottung, Federico Berto, Chuanbo Hua +9
Designing high-performing heuristics for vehicle routing problems (VRPs) is a complex task that requires both intuition and deep domain knowledge. Large language model (LLM)-based…
Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement
Haoran Ye, Jing Jin, Yuhang Xie +2
The advancement of large language models (LLMs) has outpaced traditional evaluation methodologies. This progress presents novel challenges, such as measuring human-like psychologic…
Generative Psycho-Lexical Approach for Constructing Value Systems in Large Language Models
Haoran Ye, Tianze Zhang, Yuhang Xie +4
Values are core drivers of individual and collective perception, cognition, and behavior. Value systems, such as Schwartz's Theory of Basic Human Values, delineate the hierarchy an…
Measuring Human and AI Values Based on Generative Psychometrics with Large Language Models
Haoran Ye, Yuhang Xie, Yuanyi Ren +3
Human values and their measurement are long-standing interdisciplinary inquiry. Recent advances in AI have sparked renewed interest in this area, with large language models (LLMs)…
ValueBench: Towards Comprehensively Evaluating Value Orientations and Understanding of Large Language Models
Yuanyi Ren, Haoran Ye, Hanjun Fang +2
Large Language Models (LLMs) are transforming diverse fields and gaining increasing influence as human proxies. This development underscores the urgent need for evaluating value or…
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Network
Yunbo Hou, Haoran Ye, Yingxue Zhang +2
Placement is a critical and challenging step of modern chip design, with routability being an essential indicator of placement quality. Current routability-oriented placers typical…
ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
Haoran Ye, Jiarui Wang, Zhiguang Cao +5
The omnipresence of NP-hard combinatorial optimization problems (COPs) compels domain experts to engage in trial-and-error heuristic design. The long-standing endeavor of design au…
GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time
Haoran Ye, Jiarui Wang, Helan Liang +3
The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance. This paper proposes GLOP (Globa…
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
Haoran Ye, Jiarui Wang, Zhiguang Cao +2
Ant Colony Optimization (ACO) is a meta-heuristic algorithm that has been successfully applied to various Combinatorial Optimization Problems (COPs). Traditionally, customizing ACO…
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
Federico Berto, Chuanbo Hua, Junyoung Park +30
Combinatorial optimization (CO) is fundamental to several real-world applications, from logistics and scheduling to hardware design and resource allocation. Deep reinforcement lear…