most citedMulti-Document Grounded Multi-Turn Synthetic Dialog Generation

2 citations · 4 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE2025

Live API-Bench: 2500+ Live APIs for Testing Multi-Step Tool Calling

Benjamin Elder, Anupama Murthi, Jungkoo Kang +4

Large language models (LLMs) increasingly rely on external tools and APIs to execute complex tasks specified in natural language. Evaluating such tool calling capabilities in reali…

cs.CY2025

New Tools are Needed for Tracking Adherence to AI Model Behavioral Use Clauses

Daniel McDuff, Tim Korjakow, Kevin Klyman +1

Foundation models have had a transformative impact on AI. A combination of large investments in research and development, growing sources of digital data for training, and architec…

cs.LG2025

Spotlight Your Instructions: Instruction-following with Dynamic Attention Steering

Praveen Venkateswaran, Danish Contractor

In many real-world applications, users rely on natural language instructions to guide large language models (LLMs) across a wide range of tasks. These instructions are often comple…

cs.CL20252 cited

MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems

Yannis Katsis, Sara Rosenthal, Kshitij Fadnis +7

Retrieval-augmented generation (RAG) has recently become a very popular task for Large Language Models (LLMs). Evaluating them on multi-turn RAG conversations, where the system is…

cs.CL20242 cited

Multi-Document Grounded Multi-Turn Synthetic Dialog Generation

Young-Suk Lee, Chulaka Gunasekara, Danish Contractor +2

We introduce a technique for multi-document grounded multi-turn synthetic dialog generation that incorporates three main ideas. First, we control the overall dialog flow using taxo…