10 citations · 37 across the 20 of their papers we have counts for
3 papers · 1 filter
ToolRM: Outcome Reward Models for Tool-Calling Large Language Models
Mayank Agarwal, Ibrahim Abdelaziz, Kinjal Basu +4
As large language models (LLMs) increasingly interact with external tools, reward modeling for tool use has emerged as a critical yet underexplored area of research. Existing rewar…
Putting It All into Context: Simplifying Agents with LCLMs
Mingjian Jiang, Yangjun Ruan, Luis Lastras +2
Recent advances in language model (LM) agents have demonstrated significant potential for automating complex real-world tasks. To make progress on these difficult tasks, LM agent a…
R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory
Tenghao Huang, Kinjal Basu, Ibrahim Abdelaziz +3
The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often struggle with efficient navigation…