activity
20162026
most citedNeural Structural Correspondence Learning for Domain Adaptation

8 citations · 16 across the 28 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CV2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.LG2026

Self-Improving World Modelling with Latent Actions

Yifu Qiu, Zheng Zhao, Waylon Li +4

Internal modelling of the world -- predicting transitions between previous states and next states under actions -- is essential to reasoning and planning for LLMs and V…

cs.AI2026

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,…

cs.CV2026

Lost in Space? Vision-Language Models Struggle with Relative Camera Pose Estimation

Ken Deng, Yifu Qiu, Yoni Kasten +2

We study whether vision-language models (VLMs) can solve relative camera pose estimation (RCPE) from image pairs, a direct test of multi-view spatial reasoning. We cast RCPE as a d…