23 citations · 46 across the 18 of their papers we have counts for
7 papers · 1 filter
Synthesize and Reward -- Reinforcement Learning for Multi-Step Tool Use in Live Environments
Ibrahim Abdelaziz, Asim Munawar, Kinjal Basu +4
Training LLMs to orchestrate multi-step tool calls is held back by three coupled obstacles: realistic stateful execution environments are costly to build, synthetic training querie…
Simulating Complex Multi-Turn Tool Calling Interactions in Stateless Execution Environments
Maxwell Crouse, Ibrahim Abdelaziz, Kshitij Fadnis +6
Synthetic data has proven itself to be a valuable resource for tuning smaller, cost-effective language models to handle the complexities of multi-turn tool calling conversations. W…
Few-shot Policy (de)composition in Conversational Question Answering
Kyle Erwin, Guy Axelrod, Maria Chang +8
The task of policy compliance detection (PCD) is to determine if a scenario is in compliance with respect to a set of written policies. In a conversational setting, the results of…
API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs
Kinjal Basu, Ibrahim Abdelaziz, Subhajit Chaudhury +7
There is a growing need for Large Language Models (LLMs) to effectively use tools and external Application Programming Interfaces (APIs) to plan and complete tasks. As such, there…
MISMATCH: Fine-grained Evaluation of Machine-generated Text with Mismatch Error Types
Keerthiram Murugesan, Sarathkrishna Swaminathan, Soham Dan +9
With the growing interest in large language models, the need for evaluating the quality of machine text compared to reference (typically human-generated) text has become focal atte…
Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency
Maxwell Crouse, Ramon Astudillo, Tahira Naseem +4
We introduce Logical Offline Cycle Consistency Optimization (LOCCO), a scalable, semi-supervised method for training a neural semantic parser. Conceptually, LOCCO can be viewed as…