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Collections including paper arxiv:2408.00714

Papers I want to read

Papers in my to-read list

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13 • 67
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 126
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 85

LinFusion: 1 GPU, 1 Minute, 16K Image

Paper • 2409.02097 • Published Sep 3 • 31
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion

Paper • 2409.11406 • Published Sep 17 • 25
Diffusion Models Are Real-Time Game Engines

Paper • 2408.14837 • Published Aug 27 • 121
Segment Anything with Multiple Modalities

Paper • 2408.09085 • Published Aug 17 • 21

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6 • 25
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6 • 12
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 38
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7 • 19

Papers related to web agents, screen agents, autonomous agents that can mimic human users in computer and/or web use

ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7 • 38
WebArena: A Realistic Web Environment for Building Autonomous Agents

Paper • 2307.13854 • Published Jul 25, 2023 • 23
Mind2Web: Towards a Generalist Agent for the Web

Paper • 2306.06070 • Published Jun 9, 2023 • 19
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation

Paper • 2410.13232 • Published 24 days ago • 40

AI papers to read

SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1 • 107

Prompt is text-based memory. System II prompting is updating memory. Parametric memory is long-term, while prompt-based are short-tem.

What You Say = What You Want? Teaching Humans to Articulate Requirements for LLMs

Paper • 2409.08775 • Published Sep 13
OmniQuery: Contextually Augmenting Captured Multimodal Memory to Enable Personal Question Answering

Paper • 2409.08250 • Published Sep 12 • 1
Synthetic continued pretraining

Paper • 2409.07431 • Published Sep 11 • 1
WonderWorld: Interactive 3D Scene Generation from a Single Image

Paper • 2406.09394 • Published Jun 13 • 3

scene understanding

SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1 • 107

SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1 • 107

Computer Vision

Do we still need a network for specific computer vision tasks anymore today?

SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1 • 107
facebook/sam2.1-hiera-large

Mask Generation • Updated Sep 24 • 11.2k • 38

image understanding

SAM 2: Segment Anything in Images and Videos

Paper • 2408.00714 • Published Aug 1 • 107

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