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Found 6 papers, 2 papers with code
VideoMamba: Spatio-Temporal Selective State Space Model
We introduce VideoMamba, a novel adaptation of the pure Mamba architecture, specifically designed for video recognition.
VLind-Bench: Measuring Language Priors in Large Vision-Language Models
To this end, we propose a new benchmark called VLind-Bench, which is the first benchmark specifically designed to measure the language priors, or blindness, of LVLMs.
AdvisorQA: Towards Helpful and Harmless Advice-seeking Question Answering with Collective Intelligence
Therefore, we've completed a benchmark encompassing daily life questions, diverse corresponding responses, and majority vote ranking to train our helpfulness metric.
Breaking Temporal Consistency: Generating Video Universal Adversarial Perturbations Using Image Models
To address this challenge, we introduce the Breaking Temporal Consistency (BTC) method, which is the first attempt to incorporate temporal information into video attacks using image models.
LifeTox: Unveiling Implicit Toxicity in Life Advice
As large language models become increasingly integrated into daily life, detecting implicit toxicity across diverse contexts is crucial.
Critic-Guided Decoding for Controlled Text Generation
In this work, we propose a novel critic decoding method for controlled language generation (CriticControl) that combines the strengths of reinforcement learning and weighted decoding.
