most citedGame-theoretic LLM: Agent Workflow for Negotiation Games

15 citations · 15 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CY2025

Can Online GenAI Discussion Serve as Bellwether for Labor Market Shifts?

Shurui Cao, Wenyue Hua, William Yang Wang +2

The rapid advancement of Large Language Models (LLMs) has generated considerable speculation regarding their transformative potential for labor markets. However, existing approache…

cs.AI2025

Dynamic Speculative Agent Planning

Yilin Guan, Qingfeng Lan, Sun Fei +5

Despite their remarkable success in complex tasks propelling widespread adoption, large language-model-based agents still face critical deployment challenges due to prohibitive lat…

cs.LG2025

Semantic Scheduling for LLM Inference

Wenyue Hua, Dujian Ding, Yile Gu +4

Conventional operating system scheduling algorithms are largely content-ignorant, making decisions based on factors such as latency or fairness without considering the actual inten…

cs.CL2025

THOUGHTTERMINATOR: Benchmarking, Calibrating, and Mitigating Overthinking in Reasoning Models

Xiao Pu, Michael Saxon, Wenyue Hua +1

Reasoning models have demonstrated impressive performance on difficult tasks that traditional language models struggle at. However, many are plagued with the problem of overthinkin…

cs.HC2025

REALM: A Dataset of Real-World LLM Use Cases

Jingwen Cheng, Kshitish Ghate, Wenyue Hua +3

Large Language Models (LLMs), such as the GPT series, have driven significant industrial applications, leading to economic and societal transformations. However, a comprehensive un…

cs.AI202415 cited

Game-theoretic LLM: Agent Workflow for Negotiation Games

Wenyue Hua, Ollie Liu, Lingyao Li +9

This paper investigates the rationality of large language models (LLMs) in strategic decision-making contexts, specifically within the framework of game theory. We evaluate several…