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MotionLLM: Understanding Human Behaviors from Human Motions and Videos
Paper • 2405.20340 • Published • 20 -
Spectrally Pruned Gaussian Fields with Neural Compensation
Paper • 2405.00676 • Published • 9 -
Paint by Inpaint: Learning to Add Image Objects by Removing Them First
Paper • 2404.18212 • Published • 28 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 120
Collections
Discover the best community collections!
Collections including paper arxiv:2501.01957
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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 22 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
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2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 93 -
CodeElo: Benchmarking Competition-level Code Generation of LLMs with Human-comparable Elo Ratings
Paper • 2501.01257 • Published • 46 -
Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models
Paper • 2501.01423 • Published • 36 -
REDUCIO! Generating 1024times1024 Video within 16 Seconds using Extremely Compressed Motion Latents
Paper • 2411.13552 • Published
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LongVILA: Scaling Long-Context Visual Language Models for Long Videos
Paper • 2408.10188 • Published • 51 -
xGen-MM (BLIP-3): A Family of Open Large Multimodal Models
Paper • 2408.08872 • Published • 98 -
Building and better understanding vision-language models: insights and future directions
Paper • 2408.12637 • Published • 124 -
Show-o: One Single Transformer to Unify Multimodal Understanding and Generation
Paper • 2408.12528 • Published • 51
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iVideoGPT: Interactive VideoGPTs are Scalable World Models
Paper • 2405.15223 • Published • 13 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 54 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 87 -
Matryoshka Multimodal Models
Paper • 2405.17430 • Published • 31
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 41 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
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VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction
Paper • 2501.01957 • Published • 38 -
From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities
Paper • 2410.02155 • Published • 2 -
OpenOmni: Large Language Models Pivot Zero-shot Omnimodal Alignment across Language with Real-time Self-Aware Emotional Speech Synthesis
Paper • 2501.04561 • Published • 16
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2.5 Years in Class: A Multimodal Textbook for Vision-Language Pretraining
Paper • 2501.00958 • Published • 93 -
ProgCo: Program Helps Self-Correction of Large Language Models
Paper • 2501.01264 • Published • 24 -
VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction
Paper • 2501.01957 • Published • 38 -
BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning
Paper • 2501.03226 • Published • 34