18 papers
UniProbe: A Learnable Token-Level Hallucination Detector for Large VLMs using Multi-Structural Internal Representations
Dvir Samuel, Guy Bar-Shalom, Fabrizio Frasca +4
Large Vision-Language Models (LVLMs) achieve impressive visual reasoning and dialogue capabilities, yet frequently hallucinate content unsupported by the visual input. Effective mi…
Paved with True Intents: Intent-Aware Training Improves LLM Safety Classification Across Training Regimes
Jeremias Ferrao, Niclas Müller-Hof, Iustin Sîrbu +2
We argue that safety classifiers should model user intent as an explicit signal between the prompt and the final label. To study this, we introduce AIMS, a human-annotated dataset…
Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles
Shun Shao, Zheng Zhao, Anna Korhonen +2
Most fairness research in NLP assumes direct access to protected attributes such as gender, race, or nationality. In practice, however, such information is often unavailable due to…
Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics
Yifu Qiu, Yftah Ziser, Anna Korhonen +2
Can unified vision-language models (VLMs) perform forward dynamics prediction (FDP), i.e., predicting the future state (in image form) given the previous observation and an action…
When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation
Mingyan Wu, Han Yang, Omer Ben-Porat +1
Retrieval-Augmented Generation (RAG) typically assumes that external knowledge is free, but many high-quality sources are paywalled, licensed, restricted, or otherwise costly to ac…
From Competition to Collaboration: Designing Sustainable Mechanisms Between LLMs and Online Forums
Niv Fono, Yftah Ziser, Omer Ben-Porat
While Generative AI (GenAI) systems draw users away from (Q&A) forums, they also depend on the very data those forums produce to improve their performance. Addressing this paradox,…