Webinar by: Marco Valentino (University of Sheffield)

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Dear colleague,

We are happy to announce the next webinar in the Language Technology 
webinar series organized by The HiTZ Chair of Artificial Intelligence 
and Language Technology (https://hitz.eus/katedra). We are organizing 
one seminar every month. This will be the final event for this cycle, 
but we will return with a new series next October. Have a great summer!

Speaker: Marco Valentino (University of Sheffield)
Title: Reconciling Plausible and Formal Reasoning in Large Language Models
Date: Thursday, July 2, 2026 - 15:00 CET

Summary: A persistent challenge in AI is the effective integration of 
plausible and formal reasoning - the former concerning the plausibility 
and contextual relevance of arguments, the latter focusing on their 
logical and structural validity. Large Language Models (LLMs) are not 
immune to such a challenge. By virtue of their extensive pre-training, 
LLMs can generate plausible and linguistically fluent arguments, but 
struggle with the systematicity and consistency required for robust 
logical reasoning. At the same time, LLMs offer new opportunities to 
study and overcome this intrinsic conflict. This talk will focus on such 
opportunities, presenting different research directions aimed at 
reconciling plausible and formal reasoning, including LLM-driven 
neuro-symbolic integration, quasi-symbolic abstractions, and latent 
circuit disentanglement. The final part of the talk will discuss the 
persisting challenges in achieving truly unified reasoning and outline 
possible directions for future research in the field.

Bio: Marco is a Lecturer in Artificial Intelligence and Applications of 
AI in the Natural Language Processing (NLP) group at the University of 
Sheffield. Prior to Sheffield, he was a member of the Neuro-Symbolic AI 
Group at the Idiap Research Institute in Switzerland, and obtained a PhD 
in Computer Science from the University of Manchester. His research 
focuses on developing AI systems that can use explanation as a core 
mechanism for learning and reasoning, investigating the integration of 
neural and symbolic AI methods. Moreover, he is interested in developing 
methodologies to interpret, control, and evaluate Large Language Models 
(LLMs), with a focus on disentangling knowledge acquisition from 
abstract logical reasoning, and enabling out-of-distribution, 
out-of-domain generalisation.

Registration: https://www.hitz.eus/webinar_izenematea

You can view the videos of previous webinars and the schedule for 
upcoming webinars here: http://www.hitz.eus/webinars

If you cannot attend this seminar, but you want to be informed of the 
following HiTZ webinars, please complete this registration form instead: 
http://www.hitz.eus/webinar_info

Best wishes,

The HiTZ Chair of Artificial Intelligence and Language Technology

P.S: HiTZ will not grant any type of certificate for attendance at these 
webinars.

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