• 1
• 0
• 0

Seed1.5-VL

Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning, achieving state-of-the-a...

• 1
• 0
• 0

cudaLLM

• 1
• 0
• 0

Seed-X-7B

• 1
• 0
• 0

EvaLearn

EvaLearn is a pioneering benchmark designed to evaluate large language models (LLMs) on their learning capability and efficiency in challenging tasks.

• 1
• 0
• 0

Chain-of-Action

Official implementation of Chain-of-Action: Trajectory Autoregressive Modeling for Robotic Manipulation. Accepted in NeurIPS 2025.

• 1
• 0
• 0

SeedVR

Repo for SeedVR2 (ICLR2026) & SeedVR (CVPR2025 Highlight)

• 1
• 0
• 0

StragglerAnalysis

• 1
• 0
• 0

BM-code

[Arxiv 2025] ByteMorph: Benchmarking Instruction-Guided Image Editing with Non-Rigid Motions

• 1
• 0
• 0

DeepFlow

[ICCV 2025] Deeply Supervised Flow-Based Generative Models

• 1
• 0
• 0

Seed-Coder

Seed-Coder is a family of lightweight open-source code LLMs comprising base, instruct and reasoning models, developed by ByteDance Seed.

• 1
• 0
• 0

SAIL

Implementation for "The Scalability of Simplicity: Empirical Analysis of Vision-Language Learning with a Single Transformer"

• 1
• 0
• 0

Bagel

Open-source unified multimodal model

• 1
• 0
• 0

Triton-distributed

Distributed Compiler and Optimized Parallel Kernels

• 1
• 0
• 0

Seed-Thinking-v1.5

• 1
• 0
• 0

VideoWorld

[CVPR 2025] VideoWorld is a simple generative model that learns purely from unlabeled videos—much like how babies learn by observing their environm...

• 1
• 0
• 0

VeOmni

VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo

• 1
• 0
• 0

ByteCheckpoint

ByteCheckpoint: An Unified Checkpointing Library for LFMs

• 1
• 0
• 0

Agent-R

Resources for our paper: "Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training"

• 1
• 0
• 0

FlexPrefill

Code for paper: [ICLR2025 Oral] FlexPrefill: A Context-Aware Sparse Attention Mechanism for Efficient Long-Sequence Inference

• 1
• 0
• 0

ShadowKV

[ICML 2025 Spotlight] ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference