{"as_of":"2026-08-09T19:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1625e281180f35e17165067d26d084d7569f3c32ee577d646ae287e2a689935c","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T12:30:32.026111Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.24762/citation-record","integrity":"/paper/2607.24762/integrity","json":"/paper/2607.24762/citation-record.json","paper":"/paper/2607.24762"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.178857Z","title":"Efficient processing of deep neural networks: A tutorial and survey,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.178857Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:a563cf7d465770c1187381694e43d32fbf48216122bc8b18f8341de6f900a0e4","observation_id":"1971731f-9819-49a5-9d68-e18cae51aae1","resolution":{"observed_at":"2026-08-02T12:30:26.178857Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.321349Z","title":"In-datacenter performance analysis of a tensor processing unit,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.321349Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:e80ca04bd24a88049dab2cd1ba2e30b7a4f473839a56ba726ddab29d420f6b2b","observation_id":"25925247-bfd9-4f71-9fcc-0ae754836ca7","resolution":{"observed_at":"2026-08-02T12:30:26.321349Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.464343Z","title":"A systematic characterization of LLM inference on GPUs,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.464343Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:c96d0ed8f0f387f972ff782e6dfaafb23c2c2a20c16bd7d637cc0d8636c2e95f","observation_id":"8f6ff40f-c41e-42ba-b3db-daef252ba32a","resolution":{"observed_at":"2026-08-02T12:30:26.464343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.606355Z","title":"Triton: An intermediate language and compiler for tiled neural network computations,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.606355Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:ed6660230a32e69a19d07f1153f0a6c98d9b915c65c4b79d61ffa40039e0b994","observation_id":"1f88046d-bd44-410c-b9e8-366468ef7862","resolution":{"observed_at":"2026-08-02T12:30:26.606355Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.776342Z","title":"FlashAttention: Fast and memory-efficient exact attention with IO-awareness,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.776342Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:95d205b3a1e3a2f1f677b226cd58af9e7065b0b67bcf790665ff55998c229bdb","observation_id":"a7dec49e-6593-424e-b528-9b37879f9239","resolution":{"observed_at":"2026-08-02T12:30:26.776342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:26.916959Z","title":"Autocomp: A powerful and portable code optimizer for tensor accelerators,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:26.916959Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:cbecb3f2220514f41da331fa66884904812f2b7a5b4e279393f0126a09eaaf19","observation_id":"15a5c079-575a-4971-9bb1-0ae777476a47","resolution":{"observed_at":"2026-08-02T12:30:26.916959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.23194","last_updated":"2025-07-31T02:26:58Z","snapshot_observed_at":"2026-08-09T05:05:37.816527Z","submitted_at":"2025-07-31T02:26:58Z","title":"Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.23194","snapshot_observed_at":"2026-08-02T12:30:27.102520Z","title":"GEAK: Introducing Triton kernel AI agent and evaluation benchmarks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.102520Z"},"links":{"cited_paper":"/paper/2507.23194","citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:149660a1b5e97faab6d8c816485510ddaae2830de98e641b512d1185ebe201ae","observation_id":"6a424d0a-ac69-4f2d-9e89-e7c6f562f746","resolution":{"observed_at":"2026-08-02T12:30:27.102520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:27.269678Z","title":"KernelBench: Can LLMs write efficient GPU kernels?","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.269678Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:ef6569f129757d6dc50b062bae8b0df458bf2bbe8918e7b8db67facff9149ddd","observation_id":"7acecd29-b2f7-4157-84bb-80508cd4c738","resolution":{"observed_at":"2026-08-02T12:30:27.269678Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.04956","last_updated":"2026-05-11T05:42:58Z","snapshot_observed_at":"2026-07-31T06:44:33.288553Z","submitted_at":"2026-05-06T14:18:36Z","title":"KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.04956","snapshot_observed_at":"2026-08-02T12:30:27.349032Z","title":"Kernel- BenchX: A comprehensive benchmark for evaluating LLM-generated GPU kernels,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.349032Z"},"links":{"cited_paper":"/paper/2605.04956","citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:a025d77bdad46de09dd45f7ae417a0716d408c2d5addc6627a7b1028e5834d05","observation_id":"ebf936cc-483d-4676-a6c9-198a92e5bff9","resolution":{"observed_at":"2026-08-02T12:30:27.349032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:27.467840Z","title":"TritonBench: Benchmarking large language model capabilities for generating Triton operators,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.467840Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:fbf03245472db76203752bef5af47f5f1483a7752e16a40d3050cbdfebaaee32","observation_id":"cf8a3bc0-b548-4ab6-a1ce-11250e5c3b1c","resolution":{"observed_at":"2026-08-02T12:30:27.467840Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.17773","last_updated":"2025-07-26T08:05:03Z","snapshot_observed_at":"2026-08-06T15:45:36.957899Z","submitted_at":"2025-07-20T00:58:33Z","title":"MultiKernelBench: A Multi-Platform Benchmark for Kernel Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.17773","snapshot_observed_at":"2026-08-02T12:30:27.620409Z","title":"MultiKernelBench: A multi-platform benchmark for kernel generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.620409Z"},"links":{"cited_paper":"/paper/2507.17773","citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:d65fa380051e35ad0ad44a77bde22bd6f4742063ecbd9c084d074e6d7cda317a","observation_id":"ee1d5d5f-ffef-448f-ba1b-f08fa11edc70","resolution":{"observed_at":"2026-08-02T12:30:27.620409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:27.759973Z","title":"CUDABench: Benchmarking LLMs for text-to-CUDA generation,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.759973Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:917de2083f12d719879c2416d6f37f57cc6d211840d8220bb4f45a496197db41","observation_id":"3e4ec3f7-dd9f-4493-8e70-bb36463823a5","resolution":{"observed_at":"2026-08-02T12:30:27.759973Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:27.914125Z","title":"BackendBench: An evaluation suite for testing how well LLMs and humans can write PyTorch backends,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:27.914125Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:36279ffeae0f81efdf9745f6b60885e8843a2a24495b2be164937e83347a63ba","observation_id":"69e3f430-ff49-4f17-b5fa-381b2505f563","resolution":{"observed_at":"2026-08-02T12:30:27.914125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:28.074757Z","title":"FlashInfer- Bench: Building the virtuous cycle for AI-driven LLM systems,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:28.074757Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:d573d3912371dce3c4c3c02986b275af74706c4ec6657924e2b0ad5a1ddc1f1b","observation_id":"ac666df2-100b-4f17-85ff-b6bada40bcdd","resolution":{"observed_at":"2026-08-02T12:30:28.074757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:28.230400Z","title":"CudaForge: An agent framework with hardware feedback for CUDA kernel optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:28.230400Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:45adbba6ce0dd3eba6b954bbdea922a6ef238708dfe13ba24edf8833c8e48584","observation_id":"5a3d9507-9764-4c7b-8de6-db46453091de","resolution":{"observed_at":"2026-08-02T12:30:28.230400Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:28.429142Z","title":"Astra: A multi-agent system for GPU kernel performance optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:28.429142Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:aa27cf094515f4813feb755fcf58b97fb21a6ad4ac2c91b9ced22493b958565c","observation_id":"4d0106e1-eee0-4b52-b862-7efe271f87e9","resolution":{"observed_at":"2026-08-02T12:30:28.429142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:28.664212Z","title":"Towards robust agentic CUDA kernel benchmarking, verification, and optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:28.664212Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:356421130d25e996bf233252cf741bd3a486e1b2b2cb74a531a393b3a6c11b3c","observation_id":"aac71d27-5e89-449f-8141-48457486147d","resolution":{"observed_at":"2026-08-02T12:30:28.664212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:28.844946Z","title":"KernelAgent: Multi-agent GPU kernel synthesis and optimization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:28.844946Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:817eba79816be4d687808ddd4263dd38cd17e4bea2cedf26eb7d740c1a17e918","observation_id":"fe5c0d64-fea4-4f74-8e62-feac4f59f4eb","resolution":{"observed_at":"2026-08-02T12:30:28.844946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.054222Z","title":"Complete anytime beam search,","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.054222Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:d94136ae60e92af347ebfca0ec5b29e8694541ad67be9f5620d80a820ce96d80","observation_id":"0ab9e2cb-02dd-42ab-8e22-1d56bed21f32","resolution":{"observed_at":"2026-08-02T12:30:29.054222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.198605Z","title":"Bandit based Monte-Carlo planning,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.198605Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:c859bfb117100235e0defcf745af0a390f67a6e41ea70595c6d8379c8b120161","observation_id":"2048d913-47f0-4260-a38a-f78686939b10","resolution":{"observed_at":"2026-08-02T12:30:29.198605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.351224Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.351224Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:e30ba231dc0800497637f16d422b9ab0d5f0284a560b6fd3b2f64063fe30be11","observation_id":"e2ad9d42-aa80-443c-96ed-3d5a88a17e51","resolution":{"observed_at":"2026-08-02T12:30:29.351224Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.480014Z","title":"Stable diffusion 3.5 medium model card,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.480014Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:cec9b856a39faa0b67c0faa9bbedf8d8b1ee742ec9dfa47b81b740deeda8b959","observation_id":"011e335f-1c45-452f-8c61-007d0a3eb00e","resolution":{"observed_at":"2026-08-02T12:30:29.480014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.623340Z","title":"google/gemma-4-E2B-it model card,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.623340Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:0ea0b5f0cab089bc505e5866bddbc181b134ca2cbb621259816a1fed4625ea0c","observation_id":"4017e7e9-ff10-478a-9d07-2d1bca640a3d","resolution":{"observed_at":"2026-08-02T12:30:29.623340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.773982Z","title":"Qwen/Qwen3.5-35B-A3B model card,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.773982Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:86abd1920c9743ada1e0730bcbd401e71d0d3caa93005fcac8f224d878a67088","observation_id":"6d253fc1-25e5-470c-9124-7871f2c466a5","resolution":{"observed_at":"2026-08-02T12:30:29.773982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:29.922278Z","title":"DGX Spark user guide: Hardware overview,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:29.922278Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:9ae3045694b263c0cb27710f6ac236da713b9d7321f419ed468fb86334cb96b5","observation_id":"609c88c6-3c38-4e72-9a5a-366e94dc4271","resolution":{"observed_at":"2026-08-02T12:30:29.922278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.071296Z","title":"PyTorch: An imperative style, high-performance deep learning library,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.071296Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:6606d5d04ca84da32646e32d593049b111a26c34f995382ad50eba28ad2cac8a","observation_id":"6a393e69-32a8-42b0-a8ce-719a6f99849d","resolution":{"observed_at":"2026-08-02T12:30:30.071296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.262483Z","title":"CUDA programming guide,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.262483Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:8dd348255963ed7323e35f6db752b6ece6258f9dcea1eb9d436b1f469ccdf8e8","observation_id":"5f81cf21-94c3-4506-b1ea-468383c6dd30","resolution":{"observed_at":"2026-08-02T12:30:30.262483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.467461Z","title":"CUDA C++ best practices guide,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.467461Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:ba284d52f032b6ed717748fec466482c64d5c0972cc57cd96a15f5b71b3ca014","observation_id":"d5a7e942-9b8c-4e34-b1b7-3bb10392d673","resolution":{"observed_at":"2026-08-02T12:30:30.467461Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.689021Z","title":"Tvm: an automated end-to-end optimizing compiler for deep learning,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.689021Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:11e6de638a09f96636fdde33ee7455a14b61334f4433aa015e19ff2cfc401c0f","observation_id":"892d299e-27b6-4fa5-99b7-d48e9eae8511","resolution":{"observed_at":"2026-08-02T12:30:30.689021Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.863019Z","title":"Learning to optimize tensor programs,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.863019Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:96dfec0607ec7f8563e5e2fd97f0e5a6b69cde7834d4e23db026076ec814df6e","observation_id":"8ca0e47d-8324-4a05-80b1-edbf8bed4ac3","resolution":{"observed_at":"2026-08-02T12:30:30.863019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:30.945666Z","title":"Ansor: Generating high-performance tensor programs for deep learning,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:30.945666Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:03234f2d6a3ac282db20689822f53bc9f883be2848e7affd2d8145dff6e41a7b","observation_id":"789fd873-2679-4da6-bbdf-b6265dc57771","resolution":{"observed_at":"2026-08-02T12:30:30.945666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.004673Z","title":"torchvision.models.resnet50,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.004673Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:cae607c0e7afd89555e8ae7a6d25753096a8308570c8fa8adc5b8501af86d9f3","observation_id":"4beaeafd-b4d0-40dd-b4e0-4a78a707faa8","resolution":{"observed_at":"2026-08-02T12:30:31.004673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.089960Z","title":"Do ImageNet classifiers generalize to ImageNet?","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.089960Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:37eb5fb6080aa76cfba60e73266c655dcca50addd02e79ac84e1984de161cbbb","observation_id":"fe150bee-c4ab-46e3-ad8c-94d2388a9e38","resolution":{"observed_at":"2026-08-02T12:30:31.089960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.198319Z","title":"Diffusers: State-of-the-art diffusion models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.198319Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:7187d46d7434fc753d1f29b0b6bc28444ad183c146c2b43cae23bde645049d1a","observation_id":"285896f3-d2c6-45cc-8af3-49dd7d60f4de","resolution":{"observed_at":"2026-08-02T12:30:31.198319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.304018Z","title":"T2I-CompBench: A comprehensive benchmark for open-world compositional text-to-image generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.304018Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:5ef358df8e2423fb93042ce5f98c9b06b8bc0e91a23e2f28e60b01ef689b165d","observation_id":"27ebcfc4-0ac0-4268-af58-72fa2a32ac8a","resolution":{"observed_at":"2026-08-02T12:30:31.304018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.421596Z","title":"Judging LLM-as-a-judge with MT-Bench and chatbot arena,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.421596Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:3a3dc36338401e6fdec0b33075d518d1a54801b0bb9fad871501d961a287c145","observation_id":"7a74e52e-c2df-4419-9e66-851ad5d55655","resolution":{"observed_at":"2026-08-02T12:30:31.421596Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.503958Z","title":"ShareGPT Prompts Annotated,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.503958Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:3878741558e2cd4ebfb8c52532ad52cad16506705c7be60405e74d62abb03e3a","observation_id":"f84e7605-fc9a-495a-8aeb-063b34e1af03","resolution":{"observed_at":"2026-08-02T12:30:31.503958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.572369Z","title":"LongBench: A bilingual, multitask benchmark for long context understanding,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.572369Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:103e9584c8397c0bb96e11644efecdb528a762156c9049b55d91c8bee8382d79","observation_id":"4060d277-5e4e-4587-ae63-2cc4018ec38f","resolution":{"observed_at":"2026-08-02T12:30:31.572369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.639521Z","title":"Introducing Claude Opus 4.7,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.639521Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:3fcf9c8638f552fa4850c23846b0c2a9aadd442260a8e1bd290c26f536e08519","observation_id":"cf6d4265-ee8b-49e5-9bff-8447c34efbdd","resolution":{"observed_at":"2026-08-02T12:30:31.639521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.722780Z","title":"ComputeEval: Evaluating large language models on CUDA,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.722780Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:ee02b80a39255df034bff5534b91273ed32ccd51bb9137234cabf8e69c0d464a","observation_id":"3959a1e7-6f4b-46f4-a12e-07b16174161a","resolution":{"observed_at":"2026-08-02T12:30:31.722780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.824296Z","title":"TritonGym: A benchmark for agentic LLM work- flows in Triton GPU code generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.824296Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:ae6358b6a08120b41b9ad3988e4c3b470e313cee5e8f3d7cb2b95c7ef42e7dd5","observation_id":"a9385890-c6d1-44c0-a485-d3b9b9803913","resolution":{"observed_at":"2026-08-02T12:30:31.824296Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:31.939574Z","title":"KernelFalcon: Deep agent architecture for autonomous GPU kernel generation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:31.939574Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:59ebcd55427ca9c0e3d4eaea86acb6b305406e9998a1f55927bdc6e7f02a167f","observation_id":"a25549b0-c343-4c98-94ed-a52768766abf","resolution":{"observed_at":"2026-08-02T12:30:31.939574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T12:30:32.026111Z","title":"torch.nn.functional.scaled_dot_product_attention,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-02T12:30:32.026111Z"},"links":{"citing_paper":"/paper/2607.24762"},"observation_digest":"sha256:39844de59854e95c4feb6c525fcbafb3da221074e02ee7b9a935f154f7856a35","observation_id":"87976858-c3f5-40f1-abef-9948308b0a7e","resolution":{"observed_at":"2026-08-02T12:30:32.026111Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.24762","last_updated":"2026-06-02T14:16:58Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T18:19:23.822393Z","submitted_at":"2026-06-02T14:16:58Z","title":"Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":43,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":43},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.24762."}