[AI Seminar Series] REMINDER: Seminar by Prof. Yue Dong, tomorrow Friday April 24th, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

Reminder for the AI Seminar tomorrow; please use the link below to register
if you plan to attend.

Best,
V. Tsotras
--------------------------

On Sun, Apr 19, 2026 at 10:01 PM Vassilis Tsotras <vassilis.tsotras at ucr.edu>
wrote:

> The next AI Seminar will be on Friday April 24th, 12-1pm, in the MRB
> Seminar Room (1st floor).
>
> *** Pizza and refreshments will be provided ****
>
> To keep track of the number of attendees, please *register* at:
> https://www.eventbrite.com/e/ai-seminar-series-tickets-1987802297181
>
> The talk will be given by *Prof. Yue Dong,* Department of Computer
> Science and Engineering, UCR
>
> TITLE: Revealing Hidden Vulnerabilities in Long-Context Large Language
> Models
>
> ABSTRACT:
> Large Language Models are increasingly deployed in applications that
> require reasoning over long and complex context, such as extended
> documents, multi-turn interactions, retrieved evidence, and multimodal
> inputs. While these capabilities make LLMs more powerful, they also
> introduce new and underexplored safety risks. In long-context settings,
> safety-relevant signals can be diluted or overridden, boundaries between
> context segments can break down, and harmful influence can emerge only when
> information is recombined during reasoning.
>
> In this talk, I will highlight recent research uncovering hidden
> vulnerabilities in long-context LLMs, including hallucinations, alignment
> failures, and adversarial weaknesses across both text and multimodal
> systems. These findings suggest that many existing safety evaluations and
> defenses, which are often designed for short and self-contained inputs, are
> insufficient for long-context reasoning. Addressing these challenges
> requires new benchmarks, interpretability tools, and defense strategies for
> safer and more reliable LLMs.
>
>
> Bio:
> Yue Dong is an Assistant Professor of Computer Science at the University
> of California, Riverside. Her research focuses on building controllable,
> trustworthy, and efficient large language models. She has published over 40
> peer-reviewed papers in leading venues including ACL, ICLR, ICML, TACL,
> NAACL, EMNLP, and AAAI. Her recent work spans hallucination reduction,
> efficient post-training, and AI safety and robustness, including
> red-teaming and alignment of multimodal language models. Her research has
> received multiple recognitions, including a Best Paper Award at the 2023
> SoCal NLP Symposium for work on multimodal LLM safety. Prior to joining UC
> Riverside, she completed PhD research internships at Google, Microsoft, and
> AI2.
>
> ------------------------------------
> Sponsored by the RAISE at UCR Institute, the AI Seminar Series presents
> speakers working on cutting edge Foundational AI or applying AI in their
> research. The goal of these seminars is to inform the UCR community about
> current trends in AI research and promote collaborations between faculty
> in this emerging field. These seminars are open to interested faculty and
> graduate/undergraduate students. Please forward this email to other
> colleagues or students in your lab that may be interested. After the
> seminar a discussion will follow for questions, open problems, ideas for
> possible collaborations etc.
>
> Sincerely,
> Vassilis Tsotras
> Professor, CSE Department
> co-Director, RAISE at UCR Institute
>
> Amit Roy-Chowdhury
> Professor, ECE Department
> co-Director, RAISE at UCR Institute
>
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