TinyGPT-V: Efficient Multimodal Large Language Model via Small Backbones
Paper
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2312.16862
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Published
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28
MLLM
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Unified-IO 2: Scaling Autoregressive Multimodal Models with Vision, Language, Audio, and Action
Paper • 2312.17172 • Published • 24 -
Towards Truly Zero-shot Compositional Visual Reasoning with LLMs as Programmers
Paper • 2401.01974 • Published • 4 -
From Audio to Photoreal Embodiment: Synthesizing Humans in Conversations
Paper • 2401.01885 • Published • 26 -
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Paper • 2401.01335 • Published • 61 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 73 -
Distilling Vision-Language Models on Millions of Videos
Paper • 2401.06129 • Published • 13 -
Bootstrapping LLM-based Task-Oriented Dialogue Agents via Self-Talk
Paper • 2401.05033 • Published • 14 -
LEGO:Language Enhanced Multi-modal Grounding Model
Paper • 2401.06071 • Published • 10 -
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Paper • 2401.04575 • Published • 14 -
Narrowing the Knowledge Evaluation Gap: Open-Domain Question Answering with Multi-Granularity Answers
Paper • 2401.04695 • Published • 8 -
Mixtral of Experts
Paper • 2401.04088 • Published • 152 -
Open-Vocabulary SAM: Segment and Recognize Twenty-thousand Classes Interactively
Paper • 2401.02955 • Published • 16 -
Understanding LLMs: A Comprehensive Overview from Training to Inference
Paper • 2401.02038 • Published • 59 -
Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 20 -
StrokeNUWA: Tokenizing Strokes for Vector Graphic Synthesis
Paper • 2401.17093 • Published • 18 -
InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model
Paper • 2401.16420 • Published • 54 -
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Paper • 2401.15947 • Published • 46 -
Overcoming the Pitfalls of Vision-Language Model Finetuning for OOD Generalization
Paper • 2401.15914 • Published • 7 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 41 -
Small Language Model Meets with Reinforced Vision Vocabulary
Paper • 2401.12503 • Published • 30 -
Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment
Paper • 2401.12474 • Published • 33 -
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Paper • 2401.12070 • Published • 41 -
SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities
Paper • 2401.12168 • Published • 21 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 122 -
DeepSeek-VL: Towards Real-World Vision-Language Understanding
Paper • 2403.05525 • Published • 38 -
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference
Paper • 2403.04132 • Published • 38 -
FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models
Paper • 2402.10986 • Published • 73 -
Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 74 -
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Paper • 2402.01622 • Published • 30 -
LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement
Paper • 2403.15042 • Published • 24 -
When Do We Not Need Larger Vision Models?
Paper • 2403.13043 • Published • 24 -
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Paper • 2404.07972 • Published • 41 -
Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models
Paper • 2404.07973 • Published • 28 -
BRAVE: Broadening the visual encoding of vision-language models
Paper • 2404.07204 • Published • 14 -
SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation
Paper • 2404.14396 • Published • 17 -
PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generation
Paper • 2404.13026 • Published • 21 -
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
Paper • 2404.12387 • Published • 35 -
BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 23 -
Visual Fact Checker: Enabling High-Fidelity Detailed Caption Generation
Paper • 2404.19752 • Published • 19 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 7 -
Many-Shot In-Context Learning in Multimodal Foundation Models
Paper • 2405.09798 • Published • 25