Multimodal

[24' EMNLP] TroL: Traversal of Layers for Large Language and Vision Models 2024.10.14 | Multimodal Adapter

[24' EMNLP] MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model 2024.10.14 | Multimodal Interpretability

[24' ACL] Cross-Modal Projection in Multimodal LLMs Doesn’t Really Project Visual Attributes to Textual Space 2024.10.14 | Multimodal Alignment

[24' ECCV] BLINK: Multimodal Large Language Models Can See but Not Perceive 2024.10.13 | Multimodal Benchmark Perception

[24'] Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations 2024.10.11 | Multimodal Interpretability

[24'] Towards Interpreting Visual Information Processing in Vision-Language Models 2024.10.11 | Multimodal Interpretability

[24'] Quadratic Is Not What You Need For Multimodal Large Language Models 2024.10.11 | Multimodal Efficiency Pruning

[24'] Intriguing Properties of Large Language and Vision Models 2024.10.11 | Multimodal Interpretability

[24'] PSALM: Pixelwise SegmentAtion with Large Multi-Modal Model 2024.10.07 | Multimodal Unified Segmentation

[24'] xGen-MM (BLIP-3): A Family of Open Large Multimodal Models 2024.09.10 | Multimodal Few-shot Learning Foundation Model

[23' ICML] BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models 2024.09.10 | Multimodal Foundation Model

[24'] LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models 2024.09.04 | Multimodal Attention Efficiency

[24' ECCV] FlexAttention for Efficient High-Resolution Vision-Language Models 2024.09.04 | Multimodal Attention Efficiency

[24' ECCV] FastV: An Image is Worth 1/2 Tokens After Layer 2 2024.09.03 | Multimodal Attention Efficiency

[24'] HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language Models in Resource-Constrained Environments 2024.08.27 | Multimodal Attention Efficiency

[24'] Hallucination of Multimodal Large Language Models: A Survey 2024.08.24 | Multimodal Hallucination Summary

[24' ACL Findings] Finding and Editing Multi-Modal Neurons in Pre-Trained Transformers 2024.08.23 | Multimodal Interpretability

[Summary] Multimodal Contrastive Decoding Variants (2) 2024.08.19 | Multimodal Contrastive Decoding Hallucination Summary

[24' ICLR-WS] A Concept-Based Explainability Framework for Large Multimodal Models 2024.08.19 | Multimodal Interpretability

[24'] HIO: Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization 2024.08.19 | Multimodal Contrastive Decoding Hallucination Interpretability Summary

[Summary] Multimodal Contrastive Decoding Variants (1) 2024.08.17 | Multimodal Contrastive Decoding Hallucination Summary

[24'] IBD: Alleviating Hallucinations in Large Vision-Language Models via Image-Biased Decoding 2024.08.17 | Multimodal Contrastive Decoding Hallucination Interpretability Summary

[24' CVPR] M3ID: Multi-Modal Hallucination Control by Visual Information Grounding 2024.08.17 | Multimodal Contrastive Decoding Hallucination

[24' ICML] Fool Your (Vision and) Language Model With Embarrassingly Simple Permutations 2024.08.17 | Multimodal Evaluation

[24' CVPR] VCD: Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding 2024.08.16 | Multimodal Contrastive Decoding Hallucination

[24' ICLR-WS] Skip n: A Simple Method to Reduce Hallucination in Large Vision-Language Models 2024.08.14 | Multimodal Decoding Hallucination

[24' ICLR] Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context Learning 2024.08.13 | Multimodal Evaluation In-Context Learning

[24'] VDGD: Mitigating LVLM Hallucinations in Cognitive Prompts by Bridging the Visual Perception Gap 2024.08.13 | Multimodal Decoding Hallucination

[24' CVPR] OPERA: Alleviating Hallucination in Multi-Modal Large Language Models via Over-Trust Penalty and Retrospection-Allocation 2024.07.30 | Multimodal Hallucination Interpretability

[24' CVPR] HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models 2024.07.30 | Multimodal Benchmark Hallucination

[24' ICML] Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models 2024.07.05 | Multimodal Analysis Instruction Tuning Visual Encoder

[24' CVPR] Osprey: Pixel Understanding with Visual Instruction Tuning 2024.07.05 | Multimodal Instruction Tuning Visual Encoder Visual Perception

[24'] ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models 2024.07.05 | Multimodal Visual Encoder

[24'] Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs 2024.07.05 | Multimodal Analysis Visual Encoder

[24'] LaSagnA: Language-based Segmentation Assistant for Complex Queries 2024.07.03 | Multimodal Referring Segmentation

[24' CVPR] Compositional Chain-of-Thought Prompting for Large Multimodal Models 2024.07.03 | Multimodal Chain-of-Thought

[24' CVPR] AnyRef: Multi-modal Instruction Tuned LLMs with Fine-grained Visual Perception 2024.07.03 | Multimodal Referring Segmentation Visual Grounding

[24' CVPR] PerceptionGPT: Effectively Fusing Visual Perception into LLM 2024.07.02 | Multimodal Analysis Detection Segmentation Visual Perception

[23'] LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models 2024.07.02 | Multimodal Segmentation Visual Grounding

[24'] F-LMM: Grounding Frozen Large Multimodal Models 2024.07.02 | Multimodal Chain-of-Thought Segmentation Visual Grounding

[24' ICLR] KOSMOS-2: Grounding Multimodal Large Language Models to the World 2024.07.01 | Multimodal Visual Grounding

[23' NIPS] KOSMOS-1: Language Is Not All You Need: Aligning Perception with Language Models 2024.07.01 | Multimodal Chain-of-Thought Foundation Model In-context Learning

[24' CVPR] GROUNDHOG: Grounding Large Language Models to Holistic Segmentation 2024.07.01 | Multimodal Panoptic Segmentation Segmentation Visual Grounding

[24'] GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest 2024.07.01 | Multimodal Instruction Tuning Visual Grounding

[24' ICLR] Ferret: Refer and Ground Anything Anywhere at Any Granularity 2024.07.01 | Multimodal Detection Visual Grounding

[23'] Shikra: Unleashing Multimodal LLM’s Referential Dialogue Magic 2024.06.26 | Multimodal Chain-of-Thought Detection Visual Grounding

[24'] MMStar: Are We on the Right Way for Evaluating Large Vision-Language Models? 2024.06.26 | Multimodal Benchmark Bias

[24' CVPR] VIVL: Towards Better Vision-Inspired Vision-Language Models 2024.06.25 | Multimodal Adapter Prefix Tuning

[24'] Visual CoT: Unleashing Chain-of-Thought Reasoning in Multi-Modal Language Models 2024.06.25 | Multimodal Chain-of-Thought

[24' CVPR] REAL: The Neglected Tails in Vision-Language Models 2024.06.25 | Multimodal Bias RAG

[24' CVPR] PixelLLM: Pixel Aligned Language Models 2024.06.25 | Multimodal Localization

[23'] LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model 2024.06.25 | Multimodal Joint Training Prefix Tuning

[24' TMLR] Multimodal Chain-of-Thought Reasoning in Language Models 2024.06.22 | Multimodal Chain-of-Thought

[24' CVPR] PixelLM: Pixel Reasoning with Large Multimodal Model 2024.06.21 | Multimodal Reasoning Segmentation

[24' CVPR] GSVA: Generalized Segmentation via Multimodal Large Language Models 2024.06.21 | Multimodal Referring Segmentation

[24' CVPR] GLaMM: Pixel Grounding Large Multimodal Model 2024.06.21 | Multimodal Segmentation Dataset Visual Grounding

[24' CVPR] LLaFS: When Large Language Models Meet Few-Shot Segmentation 2024.06.11 | Multimodal Few-Shot Segmentation In-context Learning

[24' CVPR] LLaVA-1.5: Improved Baselines with Visual Instruction Tuning 2024.06.10 | Multimodal Adapter Instruction Tuning

[24' CVPR] Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs 2024.06.07 | Multimodal Analysis Visual Encoder

[24' CVPR] Honeybee: Locality-enhanced Projector for Multimodal LLM 2024.06.04 | Multimodal Adapter Analysis

[23'] LISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model 2024.06.02 | Multimodal Reasoning Segmentation

[24'] MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training 2024.05.29 | Multimodal Analysis In-context Learning

[23'] LISA: Reasoning Segmentation via Large Language Model 2024.05.29 | Multimodal Reasoning Segmentation

[23' NIPS] LLaVA: Visual Instruction Tuning 2024.05.28 | Multimodal Instruction Tuning

[22' NIPS] Flamingo: a Visual Language Model for Few-Shot Learning 2024.05.27 | Multimodal Foundation Model In-context Learning

[21' ICML] VL-T5: Unifying Vision-and-Language Tasks via Text Generation 2024.05.15 | Multimodal Multi-task Learning

[24'] A Survey on Multimodal Large Language Models 2024.05.14 | Multimodal Summary

Language

[24' ACL] Spectral Filters, Dark Signals, and Attention Sinks 2024.09.04 | Language Attention Interpretability

[24' ICLR] StreamingLLM: Efficient Streaming Language Models with Attention Sinks 2024.08.29 | Language Attention Efficiency

[24' ICLR] PASTA: Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs 2024.08.29 | Language Attention

[24' ICML] ACT: Unveiling and Harnessing Hidden Attention Sinks 2024.08.29 | Language Attention

[Mechanistic Interpretability] Token-wise Attribution Analysis (History of Kobayashi) 2024.08.24 | Language Interpretability Summary

[Summary] Recent Contrastive Decoding Variants (2) 2024.08.16 | Language Contrastive Decoding Summary

[Summary] Recent Contrastive Decoding Variants (1) 2024.08.15 | Language Contrastive Decoding Summary

[24' ICLR] DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models 2024.08.14 | Language Contrastive Decoding Interpretability

[23' ACL] Contrastive Decoding: Open-ended Text Generation as Optimization 2024.08.14 | Language Contrastive Decoding

[23' EMNLP] Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning 2024.08.13 | Language Interpretability

[24'] Not All Layers of LLMs Are Necessary During Inference 2024.08.13 | Language Decoding Interpretability

[24' ICML-WS] Transformers need glasses! Information over-squashing in language tasks 2024.07.26 | Language Hallucination Interpretability

[24'] The Remarkable Robustness of LLMs: Stages of Inference? 2024.07.26 | Language Interpretability

[24' TACL] Lost in the Middle: How Language Models Use Long Contexts 2024.07.26 | Language Hallucination

[24' ICLR] Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models 2024.07.26 | Language Hallucination Interpretability

[Summary] Analysis of Parameter-Efficient Fine-Tuning Techniques for Large Language Models 2024.06.24 | Language Analysis PEFT Summary

[22' ICLR] Towards a Unified View of Parameter-Efficient Transfer Learning 2024.06.24 | Language Adapter PEFT

[Summary] Brief Summary of Parameter-Efficient Fine-Tuning for Language Models 2024.06.23 | Language Adapter Tuning LoRA PEFT Prefix Tuning Prompt Tuning Summary

[22' ICLR] LoRA: Low-Rank Adaptation of Large Language Models 2024.06.23 | Language LoRA PEFT

[24' ICLR] LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention 2024.06.23 | Language PEFT Prefix Tuning

[23' ICLR] Auto-CoT: Automatic Chain of Thought Prompting in Large Language Models 2024.06.20 | Language Chain-of-Thought

[22' NIPS] Zero-shot-CoT: Large Language Models are Zero-Shot Reasoners 2024.06.19 | Language Chain-of-Thought

[22' NIPS] Chain-of-Thought Prompting Elicits Reasoning in Large Language Models 2024.06.19 | Language Chain-of-Thought

[24' ICML] Self-Rewarding Language Models 2024.06.17 | Language RLHF Self-Rewarding

[23'] RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback 2024.06.11 | Language RLAIF RLHF

[24' ICML] Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study 2024.06.11 | Language Analysis DPO PPO RLHF

[23' NIPS] Direct Preference Optimization: Your Language Model is Secretly a Reward Model 2024.06.11 | Language DPO RLHF

[19’] RLHF: Fine-Tuning Language Models from Human Preferences 2024.06.10 | Language PPO RLHF

[24'] Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding 2024.06.03 | Language Meta-Prompting

Generation

[23' ICCV] DiT: Scalable Diffusion Models with Transformers 2024.05.06 | Generation Diffusion

[22' CVPR] Stable Diffusion: High-Resolution Image Synthesis with Latent Diffusion Models 2024.05.05 | Generation Diffusion

[21' ICLR] Score-Based Generative Modeling through Stochastic Differential Equations 2024.04.13 | Generation Diffusion SBM

[22' NIPS] Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding 2024.04.06 | Generation Diffusion Text2Image

[22'] DALL-E 2: Hierarchical Text-Conditional Image Generation with CLIP Latents 2024.04.05 | Generation Diffusion Text2Image

[22' ICLR-WS] Video Diffusion Models 2024.04.03 | Generation Diffusion Text2Image Video

[22' CVPR] RePaint: Inpainting using Denoising Diffusion Probabilistic Models 2024.04.03 | Generation Diffusion

[22' PMLR] GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models 2024.04.02 | Generation Diffusion Text2Image

[22' JMLR] CDM: Cascaded Diffusion Models for High Fidelity Image Generation 2024.04.01 | Generation Diffusion

[22' PAML] SR3: Image Super-Resolution via Iterative Refinement 2024.04.01 | Generation Diffusion

[21' NIPS-WS] CFG: Classifier-free Diffusion Guidance 2024.03.30 | Generation Diffusion

[22' NIPS] CG: Diffusion Models Beat GANs on Image Synthesis 2024.03.29 | Generation Diffusion

[21' PMLR] IDDPM: Improved Denoising Diffusion Probabilistic Models 2024.03.28 | Generation Diffusion

[21' ICLR] DDIM: Denoising Diffusion Implicit Models 2024.03.26 | Generation Diffusion

[21' ICLR] DDPM: Denoising Diffusion Probabilistic Models 2024.03.19 | Generation Diffusion

Medical

[24'] M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models 2024.07.03 | Medical Multimodal Segmentation

[22' ECCV] BioViL: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing 2024.06.28 | Medical Contrastive Learning

[23'] BiomedCLIP: A Multimodal Biomedical Foundation Model Pretrained from Fifteen Million Scientific Image-text Pairs 2024.06.28 | Medical Contrastive Learning

[21'] PubMedCLIP: Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain? 2024.06.27 | Medical Contrastive Learning Dataset

[22' EMNLP] MedCLIP: Contrastive Learning from Unpaired Medical Images and Text 2024.06.27 | Medical Contrastive Learning

[Summary] List of Pre-trained CLIP Models for Medical Domain 2024.06.27 | Medical Contrastive Learning Summary

[21' ICCV] GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-Efficient Medical Image Recognition 2024.06.27 | Medical Contrastive Learning Local Attention

[22' PMLR] ConVIRT: Contrastive Learning of Medical Visual Representations from Paired Images and Text 2024.06.27 | Medical Contrastive Learning

[23' PMLR] Med-Flamingo: a Multimodal Medical Few-shot Learner 2024.06.26 | Medical In-context Learning Multimodal

[23' NIPS] LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day 2024.06.26 | Medical Dataset Multimodal

[24' CVPR] Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation 2024.06.21 | Medical Prompt Tuning Segmentation Universal Segmentation

[23'] Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation 2024.05.06 | Medical Fine-tuning SAM Segmentation

[Summary] SAM(Segment Anything) Models in Medical Domain 2024.05.04 | Medical SAM Segmentation Summary

CS285

[CS285] 13. Exploration (Part 1) 2024.06.18 | CS285 RL

[CS285] 12. Model-Based Policy Learning 2024.05.28 | CS285 RL

[CS285] 11. Model-Based Reinforcement Learning 2024.05.27 | CS285 RL

[CS285] 10. Optimal Control and Planning 2024.05.04 | CS285 RL

[CS285] 9. Advanced Policy Gradients 2024.05.04 | CS285 RL

[CS285] 8. Deep RL with Q-Functions 2024.04.24 | CS285 RL

[CS285] 7. Value Function Methods 2024.04.23 | CS285 RL

[CS285] 6. Actor-Critic Algorithms 2024.04.14 | CS285 RL

[CS285] 5. Policy Gradients 2024.04.07 | CS285 RL

[CS285] 4. Introduction to Reinforcement Learning 2024.03.28 | CS285 RL

[CS285] 2. Supervised Learning of Behaviors 2024.03.21 | CS285 RL

[CS285] 1. Introduction 2024.03.15 | CS285 RL

Vision

[23' EMNLP Findings] Text Augmented Spatial-aware Zero-shot Referring Image Segmentation 2024.10.07 | Vision Referring Image Segmentation Training-free

[23' CVPR] ZS-RS: Zero-Shot Referring Image Segmentation With Global-Local Context Features 2024.10.07 | Vision Referring Image Segmentation Training-free

[24' ECCV] SCLIP: Rethinking Self-Attention for Dense Vision-Language Inference 2024.10.07 | Vision Semantic Segmentation Training-free

[22' ECCV] MaskCLIP: Extract Free Dense Labels from CLIP 2024.07.10 | Vision Contrastive Learning Semantic Segmentation Training-free

[24' ICML] Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation 2024.07.09 | Vision Contrastive Learning Semantic Segmentation

[23' CVPR] ZegCLIP: Towards Adapting CLIP for Zero-shot Semantic Segmentation 2024.07.08 | Vision Contrastive Learning Semantic Segmentation

[23' CVPR] Teaching Matters: Investigating the Role of Supervision in Vision Transformers 2024.07.08 | Vision Analysis ViT

[22' CVPR] Splicing ViT Features for Semantic Appearance Transfer 2024.07.08 | Vision Analysis Self-supervised Learning Style Transfer

[21' ICCV] Understanding Robustness of Transformers for Image Classification 2024.07.08 | Vision Analysis ViT

[23' CVPR] GRES: Generalized Referring Expression Segmentation 2024.06.21 | Vision Referring Segmentation

[24' CVPR] Universal Segmentation at Arbitrary Granularity with Language Instruction 2024.06.18 | Vision Summary Universal Segmentation

[21' ICML] CLIP: Learning Transferable Visual Models From Natural Language Supervision 2024.05.26 | Vision Contrastive Learning

CS236n

[CS236n] 10. Evaluating Generative Models 2024.03.20 | CS236n Generation

[CS236n] 9. Score Based Models (2) 2024.03.19 | CS236n Diffusion Generation

[CS236n] 8. Score Based Models (1) 2024.03.18 | CS236n Diffusion Generation

[CS236n] 7. Energy Based Models 2024.03.17 | CS236n EBM Generation

[CS236n] 6. Generative Adversarial Networks 2024.03.16 | CS236n GAN Generation

[CS236n] 5. Normalizing Flow Models 2024.03.15 | CS236n FBM Generation

[CS236n] 4. Latent Variable Models 2024.03.10 | CS236n Generation VAE

[CS236n] 3. Maximum Likelihood Learning 2024.03.09 | CS236n Generation MLE

[CS236n] 2. Autoregressive Models 2024.03.08 | CS236n AR Generation

[CS236n] 1. Introduction to Generative Models 2024.03.08 | CS236n Generation

MIT 18.065

[MIT 18.065] 1.7. Symmetric Positive Definite Matrices 2024.03.21 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.6. Eigenvalues and Eigenvectors 2024.03.20 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.5. Orthogonal Matrices and Subspaces 2024.03.19 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.4. Elimination and A = LU 2024.03.17 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.3. The Four Fundamental Subspaces 2024.03.16 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.2. Matrix-Matrix Multiplication AB 2024.03.14 | MIT 18.065 Linear Algebra

[MIT 18.065] 1.1. Multiplication Ax Using Columns of A 2024.03.14 | MIT 18.065 Linear Algebra

Listup

Vision Model Post List 2024.07.08

Medical AI Paper Post List 2024.06.29

Multimodal Model Post List 2024.06.25

Language Model Post List 2024.06.25

Web

[HTML5] HTML 총정리 2024.03.04 | Web HTML5

Hidden

[25' ICLR] Notes 2024.05.18

Application

[Sioyek] Sioyek 사용기 2024.06.02 | Application Sioyek

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