-
Zero-Shot and Few-Shot Video Question Answering with Multi-Modal Prompts
Paper • 2309.15915 • Published • 2 -
Reformulating Vision-Language Foundation Models and Datasets Towards Universal Multimodal Assistants
Paper • 2310.00653 • Published • 3 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 7 -
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18
Collections
Discover the best community collections!
Collections including paper arxiv:2309.09958
-
Visual Instruction Tuning
Paper • 2304.08485 • Published • 13 -
LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents
Paper • 2311.05437 • Published • 48 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
Aligning Large Multimodal Models with Factually Augmented RLHF
Paper • 2309.14525 • Published • 30
-
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 22 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 44 -
ModuLoRA: Finetuning 3-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Paper • 2309.16119 • Published • 1 -
LoRA ensembles for large language model fine-tuning
Paper • 2310.00035 • Published • 2
-
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs
Paper • 2309.09582 • Published • 4 -
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Paper • 2310.13127 • Published • 11 -
Evaluating the Robustness to Instructions of Large Language Models
Paper • 2308.14306 • Published • 1
-
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Paper • 2310.16045 • Published • 14 -
HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models
Paper • 2310.14566 • Published • 25 -
SILC: Improving Vision Language Pretraining with Self-Distillation
Paper • 2310.13355 • Published • 7 -
Conditional Diffusion Distillation
Paper • 2310.01407 • Published • 20
-
Language Modeling Is Compression
Paper • 2309.10668 • Published • 82 -
Baichuan 2: Open Large-scale Language Models
Paper • 2309.10305 • Published • 19 -
Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 38 -
LMDX: Language Model-based Document Information Extraction and Localization
Paper • 2309.10952 • Published • 65
-
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18 -
TextBind: Multi-turn Interleaved Multimodal Instruction-following
Paper • 2309.08637 • Published • 7 -
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 37
-
Language Modeling Is Compression
Paper • 2309.10668 • Published • 82 -
SlimPajama-DC: Understanding Data Combinations for LLM Training
Paper • 2309.10818 • Published • 10 -
Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)
Paper • 2309.08968 • Published • 22 -
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 37
-
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18 -
Noise-Aware Training of Layout-Aware Language Models
Paper • 2404.00488 • Published • 8 -
Streaming Dense Video Captioning
Paper • 2404.01297 • Published • 11
-
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18 -
TextBind: Multi-turn Interleaved Multimodal Instruction-following
Paper • 2309.08637 • Published • 7 -
Improved Baselines with Visual Instruction Tuning
Paper • 2310.03744 • Published • 37 -
A Picture is Worth More Than 77 Text Tokens: Evaluating CLIP-Style Models on Dense Captions
Paper • 2312.08578 • Published • 16