1 citations · 1 across the 12 of their papers we have counts for
4 papers · 1 filter
Learning "Partner-Aware" Collaborators in Multi-Party Collaboration
Abhijnan Nath, Nikhil Krishnaswamy
Large Language Models (LLMs) are increasingly being deployed in agentic settings where they act as collaborators with humans. Therefore, it is increasingly important to be able to…
Collaborate, Deliberate, Evaluate: How LLM Alignment Affects Coordinated Multi-Agent Outcomes
Abhijnan Nath, Carine Graff, Nikhil Krishnaswamy
As Large Language Models (LLMs) get integrated into diverse workflows, they are increasingly being regarded as "collaborators" with humans, and required to work in coordination wit…
Dynamic Epistemic Friction in Dialogue
Timothy Obiso, Kenneth Lai, Abhijnan Nath +2
Recent developments in aligning Large Language Models (LLMs) with human preferences have significantly enhanced their utility in human-AI collaborative scenarios. However, such app…
Frictional Agent Alignment Framework: Slow Down and Don't Break Things
Abhijnan Nath, Carine Graff, Andrei Bachinin +1
AI support of collaborative interactions entails mediating potential misalignment between interlocutor beliefs. Common preference alignment methods like DPO excel in static setting…