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Found 7 papers, 6 papers with code
LaDiC: Are Diffusion Models Really Inferior to Autoregressive Counterparts for Image-to-Text Generation?
Diffusion models have exhibited remarkable capabilities in text-to-image generation.
Towards Multimodal Video Paragraph Captioning Models Robust to Missing Modality
Video paragraph captioning (VPC) involves generating detailed narratives for long videos, utilizing supportive modalities such as speech and event boundaries.
VITATECS: A Diagnostic Dataset for Temporal Concept Understanding of Video-Language Models
The ability to perceive how objects change over time is a crucial ingredient in human intelligence.
FETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation
The multi-aspect categorization of FETV enables fine-grained analysis of the metrics' reliability in different scenarios.
Holistic Sentence Embeddings for Better Out-of-Distribution Detection
On the basis of the observations that token averaging and layer combination contribute to improving OOD detection, we propose a simple embedding approach named Avg-Avg, which averages all token representations from each intermediate layer as the sentence embedding and significantly surpasses the state-of-the-art on a comprehensive suite of benchmarks by a 9. 33% FAR95 margin.
Less is More: Rethinking State-of-the-art Continual Relation Extraction Models with a Frustratingly Easy but Effective Approach
2) Balanced Tuning (BT) finetunes the model on the balanced memory data.
KNAS: Green Neural Architecture Search
Many existing neural architecture search (NAS) solutions rely on downstream training for architecture evaluation, which takes enormous computations.
