45 citations · 193 across the 32 of their papers we have counts for
6 papers · 1 filter
ALYMPICS: LLM Agents Meet Game Theory -- Exploring Strategic Decision-Making with AI Agents
Shaoguang Mao, Yuzhe Cai, Yan Xia +5
This paper introduces Alympics (Olympics for Agents), a systematic simulation framework utilizing Large Language Model (LLM) agents for game theory research. Alympics creates a ver…
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Jing Hu, Lei Wang +3
We propose the In-context Autoencoder (ICAE), leveraging the power of a large language model (LLM) to compress a long context into short compact memory slots that can be directly c…
Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration
Zhenhailong Wang, Shaoguang Mao, Wenshan Wu +3
Human intelligence thrives on cognitive synergy, where collaboration among different minds yield superior outcomes compared to isolated individuals. In this work, we propose Solo P…
Smart Word Suggestions for Writing Assistance
Chenshuo Wang, Shaoguang Mao, Tao Ge +5
Enhancing word usage is a desired feature for writing assistance. To further advance research in this area, this paper introduces "Smart Word Suggestions" (SWS) task and benchmark.…
Inference with Reference: Lossless Acceleration of Large Language Models
Nan Yang, Tao Ge, Liang Wang +5
We propose LLMA, an LLM accelerator to losslessly speed up Large Language Model (LLM) inference with references. LLMA is motivated by the observation that there are abundant identi…
Learn to Memorize: Scalable Continual Learning in Semiparametric Models with Mixture-of-Neighbors Induction Memory
Guangyue Peng, Tao Ge, Wen Luo +2
Semiparametric language models (LMs) have shown promise in various Natural Language Processing (NLP) tasks. However, they utilize non-parametric memory as static storage, which lac…