Cleanup

PyTorchConference2025_GithubRepos.json

@@ -339,7 +339,7 @@
     "homepage_link": "https://docs.letta.com"
   },
   {
-    "repo_name": "server",
+    "repo_name": "Triton Inference Server",
     "repo_link": "https://github.com/triton-inference-server/server",
     "category": "inference server",
     "github_about_section": "The Triton Inference Server provides an optimized cloud and edge inferencing solution.",
@@ -599,7 +599,7 @@
     "homepage_link": "https://hazyresearch.stanford.edu/blog/2024-10-29-tk2"
   },
   {
-    "repo_name": "kernels",
+    "repo_name": "Hugging Face Kernels",
     "repo_link": "https://github.com/huggingface/kernels",
     "category": "gpu kernels",
     "github_about_section": "Load compute kernels from the Hub"
@@ -624,13 +624,6 @@
     "github_about_section": "PyTorch building blocks for the OLMo ecosystem",
     "homepage_link": "https://olmo-core.readthedocs.io/en/latest/"
   },
-  {
-    "repo_name": "mistral-inference",
-    "repo_link": "https://github.com/mistralai/mistral-inference",
-    "category": "inference engine",
-    "github_about_section": "Official inference library for Mistral models",
-    "homepage_link": "https://mistral.ai"
-  },
   {
     "repo_name": "triSYCL",
     "repo_link": "https://github.com/triSYCL/triSYCL",
@@ -645,13 +638,6 @@
     "github_about_section": "TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels",
     "homepage_link": "https://meta-pytorch.org/tritonparse"
   },
-  {
-    "repo_name": "StreamDiffusion",
-    "repo_link": "https://github.com/cumulo-autumn/StreamDiffusion",
-    "category": "image generation",
-    "github_about_section": "StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation",
-    "homepage_link": "https://arxiv.org/abs/2312.12491"
-  },
   {
     "repo_name": "reference-kernels",
     "repo_link": "https://github.com/gpu-mode/reference-kernels",
@@ -720,13 +706,6 @@
     "category": "Basic Linear Algebra Subprograms (BLAS)",
     "github_about_section": "BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment."
   },
-  {
-    "repo_name": "Wan2.2",
-    "repo_link": "https://github.com/Wan-Video/Wan2.2",
-    "category": "video generation",
-    "github_about_section": "Wan: Open and Advanced Large-Scale Video Generative Models",
-    "homepage_link": "https://wan.video"
-  },
   {
     "repo_name": "kernels-community",
     "repo_link": "https://github.com/huggingface/kernels-community",
@@ -741,20 +720,6 @@
     "github_about_section": "Omnitrace: Application Profiling, Tracing, and Analysis",
     "homepage_link": "https://rocm.docs.amd.com/projects/omnitrace"
   },
-  {
-    "repo_name": "synthetic-data-kit",
-    "repo_link": "https://github.com/meta-llama/synthetic-data-kit",
-    "category": "synthetic data generation",
-    "github_about_section": "Tool for generating high quality Synthetic datasets",
-    "homepage_link": "https://pypi.org/project/synthetic-data-kit"
-  },
-  {
-    "repo_name": "cudnn-frontend",
-    "repo_link": "https://github.com/NVIDIA/cudnn-frontend",
-    "category": "parallel computing",
-    "github_about_section": "cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it",
-    "homepage_link": "https://developer.nvidia.com/cudnn"
-  },
   {
     "repo_name": "PipelineRL",
     "repo_link": "https://github.com/ServiceNow/PipelineRL",
@@ -762,13 +727,6 @@
     "github_about_section": "A scalable asynchronous reinforcement learning implementation with in-flight weight updates.",
     "homepage_link": "https://arxiv.org/abs/2509.19128"
   },
-  {
-    "repo_name": "cosmos-predict2.5",
-    "repo_link": "https://github.com/nvidia-cosmos/cosmos-predict2.5",
-    "category": "world model",
-    "github_about_section": "Cosmos-Predict2.5, the latest version of the Cosmos World Foundation Models (WFMs) family, specialized for simulating and predicting the future state of the world in the form of video.",
-    "homepage_link": "https://research.nvidia.com/labs/cosmos-lab/cosmos-predict2.5"
-  },
   {
     "repo_name": "kraken",
     "repo_link": "https://github.com/meta-pytorch/kraken",
@@ -788,13 +746,6 @@
     "github_about_section": "Automated bottleneck detection and solution orchestration",
     "homepage_link": "https://arxiv.org/html/2508.20258v1"
   },
-  {
-    "repo_name": "streamv2v",
-    "repo_link": "https://github.com/Jeff-LiangF/streamv2v",
-    "category": "video generation",
-    "github_about_section": "Official Pytorch implementation of StreamV2V.",
-    "homepage_link": "https://jeff-liangf.github.io/projects/streamv2v"
-  },
   {
     "repo_name": "tilus",
     "repo_link": "https://github.com/NVIDIA/tilus",
@@ -808,13 +759,6 @@
     "category": "gpu kernels",
     "github_about_section": "Fast low-bit matmul kernels in Triton"
   },
-  {
-    "repo_name": "Self-Forcing",
-    "repo_link": "https://github.com/guandeh17/Self-Forcing",
-    "category": "video generation",
-    "github_about_section": "Official codebase for \"Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion\" (NeurIPS 2025 Spotlight)",
-    "homepage_link": "https://self-forcing.github.io"
-  },
   {
     "repo_name": "TritonBench",
     "repo_link": "https://github.com/thunlp/TritonBench",
@@ -822,26 +766,6 @@
     "github_about_section": "TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators",
     "homepage_link": "https://arxiv.org/abs/2502.14752"
   },
-  {
-    "repo_name": "IMO2025",
-    "repo_link": "https://github.com/harmonic-ai/IMO2025",
-    "category": "formal mathematical reasoning",
-    "github_about_section": "Harmonic's model Aristotle achieved gold medal performance, solving 5 problems. This repository contains the lean statement files and proofs for Problems 1-5.",
-    "homepage_link": "https://harmonic.fun"
-  },
-  {
-    "repo_name": "RaBitQ",
-    "repo_link": "https://github.com/gaoj0017/RaBitQ",
-    "category": "quantization",
-    "github_about_section": "[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search",
-    "homepage_link": "https://github.com/VectorDB-NTU/RaBitQ-Library"
-  },
-  {
-    "repo_name": "torchdendrite",
-    "repo_link": "https://github.com/sandialabs/torchdendrite",
-    "category": "machine learning framework",
-    "github_about_section": "Dendrites for PyTorch and SNNTorch neural networks"
-  },
   {
     "repo_name": "triton-runner",
     "repo_link": "https://github.com/toyaix/triton-runner",
@@ -849,11 +773,6 @@
     "github_about_section": "Multi-Level Triton Runner supporting Python, IR, PTX, and cubin.",
     "homepage_link": "https://triton-runner.org"
   },
-  {
-    "repo_name": "distributed-training-guide",
-    "repo_link": "https://github.com/LambdaLabsML/distributed-training-guide",
-    "github_about_section": "Best practices & guides on how to write distributed pytorch training code"
-  },
   {
     "repo_name": "Megatron-LM",
     "repo_link": "https://github.com/NVIDIA/Megatron-LM",
@@ -895,51 +814,12 @@
     "github_about_section": "Slurm: A Highly Scalable Workload Manager",
     "homepage_link": "https://slurm.schedmd.com/"
   },
-  {
-    "repo_name": "Spurious Rewards",
-    "repo_link": "https://github.com/ruixin31/Spurious_Rewards",
-    "github_about_section": "Spurious Rewards: Rethinking Training Signals in RLVR",
-    "homepage_link": "https://arxiv.org/pdf/2506.10947"
-  },
-  {
-    "repo_name": "Qwen Code",
-    "repo_link": "https://github.com/QwenLM/qwen-code",
-    "github_about_section": "An open-source AI coding agent that lives in your terminal.",
-    "homepage_link": "https://qwen.ai/qwencode"
-  },
   {
     "repo_name": "Open Thoughts",
     "repo_link": "https://github.com/open-thoughts/open-thoughts",
     "github_about_section": "Fully open data curation for reasoning models",
     "homepage_link": "https://www.open-thoughts.ai/"
   },
-  {
-    "repo_name": "OLMOS",
-    "repo_link": "https://github.com/allenai/olmes",
-    "github_about_section": "Reproducible, flexible LLM evaluations"
-  },
-  {
-    "repo_name": "SmolLM",
-    "repo_link": "https://github.com/huggingface/smollm",
-    "github_about_section": "Everything about the SmolLM and SmolVLM family of models"
-  },
-  {
-    "repo_name": "smolagents",
-    "repo_link": "https://github.com/huggingface/smolagents",
-    "github_about_section": "smolagents: a barebones library for agents that think in code.",
-    "homepage_link": "https://huggingface.co/docs/smolagents/"
-  },
-  {
-    "repo_name": "Delta Learning",
-    "repo_link": "https://github.com/scottgeng00/delta_learning",
-    "github_about_section": "Code release for the paper \"The Delta Learning Hypothesis: Preference Tuning on Weak Data can Yield Strong Gains\"",
-    "homepage_link": "https://arxiv.org/pdf/2507.06187"
-  },
-  {
-    "repo_name": "DeepSeek-V3",
-    "repo_link": "https://github.com/deepseek-ai/DeepSeek-V3",
-    "homepage_link": "https://www.deepseek.com"
-  },
   {
     "repo_name": "Optimum",
     "repo_link": "https://github.com/huggingface/optimum",