James Chang

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upvoted 3 papers 20 days ago

AgentGym: Evolving Large Language Model-based Agents across Diverse Environments

Paper • 2406.04151 • Published Jun 6, 2024 • 22

Agent-FLAN: Designing Data and Methods of Effective Agent Tuning for Large Language Models

Paper • 2403.12881 • Published Mar 19, 2024 • 18

AgentTuning: Enabling Generalized Agent Abilities for LLMs

Paper • 2310.12823 • Published Oct 19, 2023 • 36

upvoted 3 papers about 1 month ago

SoundStorm: Efficient Parallel Audio Generation

Paper • 2305.09636 • Published May 16, 2023 • 13

Redefining Temporal Modeling in Video Diffusion: The Vectorized Timestep Approach

Paper • 2410.03160 • Published Oct 4, 2024 • 5

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Paper • 2412.05271 • Published Dec 6, 2024 • 157

upvoted 11 papers about 2 months ago

ReLU^2 Wins: Discovering Efficient Activation Functions for Sparse LLMs

Paper • 2402.03804 • Published Feb 6, 2024 • 3

PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU

Paper • 2312.12456 • Published Dec 16, 2023 • 44

ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models

Paper • 2402.13516 • Published Feb 21, 2024 • 1

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Paper • 2405.04434 • Published May 7, 2024 • 21

Neural Machine Translation by Jointly Learning to Align and Translate

Paper • 1409.0473 • Published Sep 1, 2014 • 6

Effective Approaches to Attention-based Neural Machine Translation

Paper • 1508.04025 • Published Aug 17, 2015 • 3

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 62

Multi-Token Attention

Paper • 2504.00927 • Published Apr 1 • 50

XAttention: Block Sparse Attention with Antidiagonal Scoring

Paper • 2503.16428 • Published Mar 20 • 14

Kolmogorov-Arnold Attention: Is Learnable Attention Better For Vision Transformers?

Paper • 2503.10632 • Published Mar 13 • 14

Slim attention: cut your context memory in half without loss of accuracy -- K-cache is all you need for MHA

Paper • 2503.05840 • Published Mar 7 • 3

upvoted 2 articles about 2 months ago

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Article

How to Reduce Memory Use in Reasoning Models

By and 1 other •

Mar 13

• 14

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Article

Topic 33: Slim Attention, KArAt, XAttention and Multi-Token Attention Explained – What’s Really Changing in Transformers?

By and 1 other •

Apr 4

• 14

upvoted a paper about 2 months ago

MIGE: A Unified Framework for Multimodal Instruction-Based Image Generation and Editing

Paper • 2502.21291 • Published Feb 28 • 5