1 citations · 1 across the 6 of their papers we have counts for
7 papers
Why Pretraining Fails to Share Cross-Lingual Knowledge
Adam Gaber, Uriel Dolev, Elisabeth Fittschen +3
Large Language Models (LLMs) have made remarkable progress in the processing and modeling of many languages. Yet, unlike human multilinguals, they exhibit surprisingly limited cros…
Skill Issue: Are Skills Language-Invariant in LLMs?
Bobby Cheng, Adam Gaber, Zhengyuan Liu +4
Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with different languages? This work q…
MINDGAMES: A Live Arena for Evaluating Social and Strategic Reasoning in Multi-Agent LLMs
Kevin Wang, Anna Thöni, Benjamin Kempinski +50
Large language models (LLMs) are increasingly deployed as interactive agents, yet their capacity for social and strategic reasoning over extended interaction remains poorly underst…
MEMO: Memory-Augmented Model Context Optimization for Robust Multi-Turn Multi-Agent LLM Games
Yunfei Xie, Kevin Wang, Bobby Cheng +9
Multi-turn, multi-agent LLM game evaluations often exhibit substantial run-to-run variance. In long-horizon interactions, small early deviations compound across turns and are ampli…
TextArena
Leon Guertler, Bobby Cheng, Simon Yu +3
TextArena is an open-source collection of competitive text-based games for training and evaluation of agentic behavior in Large Language Models (LLMs). It spans 57+ unique environm…
STLM Engineering Report: Dropout
Dylan Hillier, Leon Guertler, Bobby Cheng +1
In this work we explore the relevance of dropout for modern language models, particularly in the context of models on the scale of <100M parameters. We explore it's relevance first…
Super Tiny Language Models
Dylan Hillier, Leon Guertler, Cheston Tan +3
The rapid advancement of large language models (LLMs) has led to significant improvements in natural language processing but also poses challenges due to their high computational a…