PDF Viewer

BUILDER'S SANDBOX

Build This Paper

Use an AI coding agent to implement this research.

OpenAI Codex
OpenAI CodexAI Agent

Lightweight coding agent in your terminal.

Claude Code
Claude CodeAI Agent

Agentic coding tool for terminal workflows.

AntiGravity IDE
AntiGravity IDEScaffolding

AI agent mindset installer and workflow scaffolder.

Cursor
CursorIDE

AI-first code editor built on VS Code.

VS Code
VS CodeIDE

Free, open-source editor by Microsoft.

Estimated $9K - $13K over 6-10 weeks.

See exactly what it costs to build this -- with 3 comparable funded startups.

7-day free trial. Cancel anytime.

Discover the researchers behind this paper and find similar experts.

7-day free trial. Cancel anytime.

References (29)

[1]
SLA2: Sparse-Linear Attention with Learnable Routing and QAT
2026Jintao Zhang, Haoxu Wang et al.
[2]
SpargeAttention2: Trainable Sparse Attention via Hybrid Top-k+Top-p Masking and Distillation Fine-Tuning
2026Jintao Zhang, Kai Jiang et al.
[3]
Geometry-Aware Rotary Position Embedding for Consistent Video World Model
2026Chendong Xiang, Jiajun Liu et al.
[4]
Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization
2026Haocheng Xi, Shuo Yang et al.
[5]
Residual Context Diffusion Language Models
2026Yuezhou Hu, Harman M. Singh et al.
[6]
TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times
2025Jintao Zhang, Kaiwen Zheng et al.
[7]
SLA: Beyond Sparsity in Diffusion Transformers via Fine-Tunable Sparse-Linear Attention
2025Jintao Zhang, Haoxu Wang et al.
[8]
SageAttention2++: A More Efficient Implementation of SageAttention2
2025Jintao Zhang, Xiaoming Xu et al.
[9]
Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation
2025Shuo Yang, Haocheng Xi et al.
[10]
SageAttention3: Microscaling FP4 Attention for Inference and An Exploration of 8-Bit Training
2025Jintao Zhang, Jia Wei et al.
[11]
Accurate INT8 Training Through Dynamic Block-Level Fallback
2025Pengle Zhang, Jia Wei et al.
[12]
Identifying Sensitive Weights via Post-quantization Integral
2025Yuezhou Hu, Weiyu Huang et al.
[13]
SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference
2025Jintao Zhang, Chendong Xiang et al.
[14]
SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization
2024Jintao Zhang, Haofeng Huang et al.
[15]
SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration
2024Jintao Zhang, Jia Wei et al.
[16]
The Llama 3 Herd of Models
2024Abhimanyu Dubey, Abhinav Jauhri et al.
[17]
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
2024Jay Shah, Ganesh Bikshandi et al.
[18]
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
2024Huiqiang Jiang, Yucheng Li et al.
[19]
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
2023Tri Dao
[20]
Scaling Vision Transformers to 22 Billion Parameters
2023Mostafa Dehghani, J. Djolonga et al.

Showing 20 of 29 references

Founder's Pitch

"SageBwd enables efficient training with low-bit attention by reducing quantization errors, providing an alternative to full-precision models."

Model OptimizationScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

1/4 signals

2.5

Quick Build

2/4 signals

5

Series A Potential

2/4 signals

5

Sources used for this analysis

arXiv Paper

Full-text PDF analysis of the research paper

GitHub Repository

Code availability, stars, and contributor activity

Citation Network

Semantic Scholar citations and co-citation patterns

Community Predictions

Crowd-sourced unicorn probability assessments

Analysis model: GPT-4o · Last scored: 3/2/2026

Explore the full citation network and related research.

7-day free trial. Cancel anytime.

Understand the commercial significance and market impact.

7-day free trial. Cancel anytime.

Get detailed profiles of the research team.

7-day free trial. Cancel anytime.