130 citations · 248 across the 17 of their papers we have counts for
4 papers · 1 filter
Environment-free Synthetic Data Generation for API-Calling Agents
Seanie Lee, Sanjoy Chowdhury, Chao Jiang +5
Training API-calling large language model (LLM) agents demands massive amounts of high-quality trajectories. However, collecting such data at scale typically requires fully impleme…
Scaling Synthetic Task Generation for Agents via Exploration
Ram Ramrakhya, Andrew Szot, Omar Attia +6
Post-Training Multimodal Large Language Models (MLLMs) to build interactive agents holds promise across domains such as computer-use, web navigation, and robotics. A key challenge…
On the Modeling Capabilities of Large Language Models for Sequential Decision Making
Martin Klissarov, Devon Hjelm, Alexander Toshev +1
Large pretrained models are showing increasingly better performance in reasoning and planning tasks across different modalities, opening the possibility to leverage them for comple…
ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation
Fei Xia, Chengshu Li, Roberto Martín-Martín +3
Many Reinforcement Learning (RL) approaches use joint control signals (positions, velocities, torques) as action space for continuous control tasks. We propose to lift the action s…