collaborators
Showing cs.LGShow all

7 papers · 1 filter

cs.LG2025

A2Perf: Real-World Autonomous Agents Benchmark

Ikechukwu Uchendu, Jason Jabbour, Korneel Van den Berghe +15

Autonomous agents and systems cover a number of application areas, from robotics and digital assistants to combinatorial optimization, all sharing common, unresolved research chall…

cs.LG2024

Exposing Limitations of Language Model Agents in Sequential-Task Compositions on the Web

Hiroki Furuta, Yutaka Matsuo, Aleksandra Faust +1

Language model agents (LMA) recently emerged as a promising paradigm on muti-step decision making tasks, often outperforming humans and other reinforcement learning agents. Despite…

cs.LG2024

Geometric-Averaged Preference Optimization for Soft Preference Labels

Hiroki Furuta, Kuang-Huei Lee, Shixiang Shane Gu +4

Many algorithms for aligning LLMs with human preferences assume that human preferences are binary and deterministic. However, human preferences can vary across individuals, and the…

cs.LG2024

Scaling Exponents Across Parameterizations and Optimizers

Katie Everett, Lechao Xiao, Mitchell Wortsman +8

Robust and effective scaling of models from small to large width typically requires the precise adjustment of many algorithmic and architectural details, such as parameterization a…

cs.LG2024

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models

Avi Singh, John D. Co-Reyes, Rishabh Agarwal +38

Fine-tuning language models~(LMs) on human-generated data remains a prevalent practice. However, the performance of such models is often limited by the quantity and diversity of hi…

cs.LG2024

A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis

Izzeddin Gur, Hiroki Furuta, Austin Huang +4

Pre-trained large language models (LLMs) have recently achieved better generalization and sample efficiency in autonomous web automation. However, the performance on real-world web…