15 citations · 15 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
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…
Finding the Minimal Parameter Budget for Implicit Reasoning: A Data Complexity Driven Scaling Law for Language Models
Xinyi Wang, Shawn Tan, Shenbo Xu +4
Reasoning is a core capability of language models (LMs), yet it remains unclear how much model capacity is necessary to support reasoning during pretraining. In this work, we study…
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…
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…
Disentangling Memory and Reasoning Ability in Large Language Models
Mingyu Jin, Weidi Luo, Sitao Cheng +5
Large Language Models (LLMs) have demonstrated strong performance in handling complex tasks requiring both extensive knowledge and reasoning abilities. However, the existing LLM in…