10 citations · 10 across the 2 of their papers we have counts for
4 papers
h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
Sumeet Ramesh Motwani, Alesia Ivanova, Ziyang Cai +5
Large language models excel at short-horizon reasoning tasks, but performance drops as reasoning horizon lengths increase. Existing approaches to combat this rely on inference-time…
REAL: Benchmarking Autonomous Agents on Deterministic Simulations of Real Websites
Divyansh Garg, Shaun VanWeelden, Diego Caples +15
We introduce REAL, a benchmark and framework for multi-turn agent evaluations on deterministic simulations of real-world websites. REAL comprises high-fidelity, deterministic repli…
Multi-Agent Risks from Advanced AI
Lewis Hammond, Alan Chan, Jesse Clifton +41
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…
MALT: Improving Reasoning with Multi-Agent LLM Training
Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das +6
Large Language Models (LLMs) often produce answers with a single chain-of-thought, which restricts their ability to explore reasoning paths or self-correct flawed outputs in comple…