arXiv:2604.14041v1 Announce Type: new
Abstract: Daily scenarios are characterized by visual richness, requiring Multimodal Large Language Models (MLLMs) to filter noise and identify decisive visual clues for accurate reasoning. Yet, current benchmarks…
arXiv:2407.08101v5 Announce Type: replace
Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, where each turn must be stepped (i.e., prompted) by the…
arXiv:2604.13304v1 Announce Type: cross
Abstract: Understanding the internal activations of Vision Transformers (ViTs) is critical for building interpretable and trustworthy models. While Sparse Autoencoders (SAEs) have been used to extract human-inte…
arXiv:2604.13305v1 Announce Type: new
Abstract: Reward models (RMs) are inherently non-neutral value functions designed and trained to encode specific objectives, such as human preferences or text-image alignment. RMs have become crucial components of…
arXiv:2604.13398v1 Announce Type: cross
Abstract: While Aspect-based Sentiment Analysis (ABSA) systems have achieved high accuracy in identifying sentiment polarities, they often operate as “black boxes,” lacking the explicit reasoning capabilities ch…
arXiv:2503.23137v2 Announce Type: replace-cross
Abstract: Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant challenge for large vision-language models (VLMs). T…
arXiv:2604.13326v1 Announce Type: new
Abstract: The robustness of machine learning models can be compromised by spurious correlations between non-causal features in the input data and target labels. A common way to test for such correlations is to tra…
arXiv:2604.13418v1 Announce Type: cross
Abstract: Motivated by the underspecified, multi-hop nature of search queries and the multimodal, heterogeneous, and often conflicting nature of real-world web results, we introduce MERRIN (Multimodal Evidence R…
arXiv:2505.19662v3 Announce Type: replace
Abstract: This paper introduces FieldWorkArena, a benchmark for agentic AI targeting real-world field work. With the recent increase in demand for agentic AI, they are built to detect and document safety hazar…
arXiv:2604.13452v1 Announce Type: new
Abstract: Long-form visual storytelling requires maintaining continuity across shots, including consistent characters, stable environments, and smooth scene transitions. While existing generative models can produc…