NLP/논문이해 (65) 썸네일형 리스트형 [논문이해] VLIS: Unimodal Language Models Guide Multimodal Language Generation 논문명: VLIS: Unimodal Language Models Guide Multimodal Language Generation 논문 링크: https://arxiv.org/abs/2310.09767 VLIS: Unimodal Language Models Guide Multimodal Language Generation Multimodal language generation, which leverages the synergy of language and vision, is a rapidly expanding field. However, existing vision-language models face challenges in tasks that require complex linguistic under.. [논문이해] The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning 논문명: The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning 논문링크: https://arxiv.org/abs/2305.14045 The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning Language models (LMs) with less than 100B parameters are known to perform poorly on chain-of-thought (CoT) reasoning in contra.. [논문 이해] SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval 논문명: SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval 논문 링크: https://arxiv.org/abs/2109.10086 SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval In neural Information Retrieval (IR), ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using efficient approximate nearest.. [논문이해] Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval? 논문명: Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?논문 링크: https://arxiv.org/abs/2301.00184 Cap4Video: What Can Auxiliary Captions Do for Text-Video Retrieval?Most existing text-video retrieval methods focus on cross-modal matching between the visual content of videos and textual query sentences. However, in real-world scenarios, online videos are often accompanied by relevan.. [논문이해] Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval 논문명: Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval 논문링크: https://arxiv.org/abs/2202.03384 Hybrid Contrastive Quantization for Efficient Cross-View Video Retrieval With the recent boom of video-based social platforms (e.g., YouTube and TikTok), video retrieval using sentence queries has become an important demand and attracts increasing research attention. Despite the d.. [논문이해] LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models 논문명: LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models 논문링크: https://arxiv.org/abs/2309.12307 LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models We present LongLoRA, an efficient fine-tuning approach that extends the context sizes of pre-trained large language models (LLMs), with limited computation cost. Typically, training LLMs with long context sizes is .. [논문이해] CODEFUSION: A Pre-trained Diffusion Model for Code Generation ChatGPT의 파라미터 개수 공개 논란으로 뜨거운 논문인데, 논문 내용 자체도 좋은 것 같아서 가져와봅니다. 논문명: CODEFUSION: A Pre-trained Diffusion Model for Code Generation 논문링크: https://arxiv.org/abs/2310.17680v1 CodeFusion: A Pre-trained Diffusion Model for Code Generation Imagine a developer who can only change their last line of code, how often would they have to start writing a function from scratch before it is correct? Auto-regress.. [논문이해] Neural Text Generation with Unlikelihood Training 논문명: Neural Text Generation with Unlikelihood Training 논문 링크: https://openreview.net/forum?id=SJeYe0NtvH Neural Text Generation With Unlikelihood Training Neural text generation is a key tool in natural language applications, but it is well known there are major problems at its core. In particular, standard likelihood training and decoding leads to... openreview.net 아이디어만 정리합니다. 그동안 generation d.. 이전 1 2 3 4 5 6 7 ··· 9 다음
