36.2501, Confs: 1st Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models (Canada)

Tue Aug 26 13:05:02 UTC 2025

LINGUIST List: Vol-36-2501. Tue Aug 26 2025. ISSN: 1069 - 4875.

Subject: 36.2501, Confs: 1st Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models (Canada)

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Date: 25-Aug-2025
From: Nikhil Krishnaswamy [nkrishna at colostate.edu]
Subject: 1st Workshop on Optimal Reliance and Accountability in Interactions with Generative Language Models

1st Workshop on Optimal Reliance and Accountability in Interactions
with Generative Language Models
Short Title: ORIGen

Date: 10-Oct-2025 - 10-Oct-2025
Location: Montreal, Canada
Meeting URL: https://origen-workshop.github.io

Linguistic Field(s): Cognitive Science; Computational Linguistics;
Discourse Analysis; Linguistic Theories; Philosophy of Language

We are pleased to invite participation in the First Workshop on
Optimal Reliance and Accountability in Interaction with Generative
Language Models (ORIGen) to be held in conjuction with the Conference
on Language Modeling (COLM) in Montreal, Canada, on October 10, 2025!
With the rapid integration of generative AI, exemplified by large
language models (LLMs), into personal, educational, business, and even
governmental workflows, such systems are increasingly being treated as
“collaborators” with humans. In such scenarios, underreliance or
avoidance of AI assistance may obviate the potential speed,
efficiency, or scalability advantages of a human-LLM team, but
simultaneously, there is a risk that subject matter non-experts may
overrely on LLMs and trust their outputs uncritically, with
consequences ranging from the inconvenient to the catastrophic.
Therefore, establishing optimal levels of reliance within an
interactive framework is a critical open challenge as language models
and related AI technology rapidly advances.
 - What factors influence overreliance on LLMs?
 - How can the consequences of overreliance be predicted and guarded
against?
 - What verifiable methods can be used to apportion accountability for
the outcomes of human-LLM interactions?
 - What methods can be used to imbue such interactions with
appropriate levels of “friction” to ensure that humans think through
the decisions they make with LLMs in the loop?
ORIGen will examine questions of reliance, trust, confidence, and
accountability in interactions with modern generative systems from an
interdisciplinary perspective, and we seek engagement from the NLP,
AI, HCI, robotics, education, and cognitive science communities and
beyond. The workshop will feature paper presentations as well as 4
invited talks from leading AI, NLP, and HCI researchers, and a panel
discussion on the Future of Reliable and Accountable AI. More
information about the workshop can be found at:
https://origen-workshop.github.io
9:00-9:15 - Opening remarks
9:15-9:50 - Invited talk I: Andreas Vlachos is a Professor of Natural
Language Processing and Machine Learning at the Department of Computer
Science and Technology at the University of Cambridge and a Dinesh
Dhamija fellow of Fitzwilliam College. His expertise includes dialogue
modeling, automated fact-checking, imitation and active learning,
semantic parsing, and natural language generation and summarization.
9:50-11:00 - Accepted paper lightning talks: 4 minutes each + 1 minute
transition
11:00-11:15 - Coffee break
11:15-12:00 - Keynote talk: Malihe Alikhani is an Assistant Professor
at Northeastern University’s Khoury College of Engineering and
Visiting Fellow at The Center on Regulation and Markets at Brookings.
She works towards developing safe and fair AI systems that enhance
communication, decision-making, and knowledge-sharing across
disciplines and populations.
12:00-12:35 - Invited talk II: Bertram F. Malle is a Professor of
Cognitive and Psychological Sciences at Brown University. He received
the Society of Experimental Social Psychology (SESP) Outstanding
Dissertation award, an NSF CAREER award, the Decision Analysis Society
2018 best publication award, several HRI best-paper awards, and the
2019 SESP Scientific Impact Award. Malle’s research focuses on moral
psychology and human-machine interaction.
12:35-2:05 - Lunch
2:05-2:40 - Invited talk III: Q. Vera Liao is an Associate Professor
of Computer Science and Engineering at the University of Michigan, and
previously a researcher at Microsoft Research and IBM research. Her
current interests are in human-AI interaction, responsible AI and AI
transparency, with a goal of bridging emerging AI technologies and
human-centered perspectives.
2:40-3:40 - Poster Session
3:40-4:00 - Coffee break
4:00-4:45 - Panel discussion: Future of Reliable and Accountable AI
 Matthias Scheutz, Tufts University
 Jesse Thomason, University of Southern California
 Diyi Yang, Stanford University
 Matthew Marge, DARPA
4:45-5:00 - Conclusion
The list of accepted papers can be found at
https://origen-workshop.github.io/programme/

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