Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:34:26.715832Z
Paper Citation Record · LEDGER
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools
As of 21 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2504.15185.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-27T02:49:30.992755Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T18:28:49.784610Z
Reference resolution
31 of 31 outbound references displayed
- verified exact0
- verified fuzzy8
- unresolved23
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4a6652bc-d83b-4769-b606-48e71a2117a9 · outbound
This paper cites Machsuite: Benchmarks for accelerator design and customized architectures,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Machsuite: Benchmarks for accelerator design and customized architectures,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.767080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 16b397de-75e4-4fc1-a6c6-d913533b839f · outbound
This paper cites Rosetta: A realistic high-level synthesis benchmark suite for software programmable fpgas,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Rosetta: A realistic high-level synthesis benchmark suite for software programmable fpgas,
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.523164Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad2034b0-1dbf-424d-a213-f999bedb445a · outbound
This paper cites Rodinia: A benchmark suite for heterogeneous computing,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Rodinia: A benchmark suite for heterogeneous computing,
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.531075Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5413d6a-256b-436a-9f3f-a5359a0afd56 · outbound
This paper cites PolyBench.
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.739489Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9e020064-1560-4a4f-969a-0ea67cbc696b · outbound
This paper cites Overgen: Improving fpga usability through domain- specific overlay generation,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Overgen: Improving fpga usability through domain- specific overlay generation,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.720088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a7f343ba-ac23-4bd9-9782-95bc15b2dfa0 · outbound
This paper cites Tapa: A scalable task-parallel dataflow programming framework for modern fpgas with co-optimization of hls and physical design,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Tapa: A scalable task-parallel dataflow programming framework for modern fpgas with co-optimization of hls and physical design,
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.565291Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 552a8f87-48ac-4e28-aa7f-76468548da25 · outbound
This paper cites Heterocl: A multi-paradigm programming infrastructure for software-defined reconfigurable computing,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Heterocl: A multi-paradigm programming infrastructure for software-defined reconfigurable computing,
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.572130Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f14e16b-3229-4361-8ed6-374e0e422eab · outbound
This paper cites Dsagen: Synthesizing programmable spatial accelerators,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Dsagen: Synthesizing programmable spatial accelerators,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.688398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 8d68b888-d04e-47b2-bcca-5b0e6d3c3db1 · outbound
This paper cites Vitis hls,.
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.662878Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation bd424098-dedd-4b70-86e6-f82f2c76bf99 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools LLaMA: Open and Efficient Foundation Language Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.590819Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9673d446-7a4b-479e-b11d-49cc5b6dc75d · outbound
This paper cites Improving language understanding by generative pre-training,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Improving language understanding by generative pre-training,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.640573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 724c2250-b578-4621-ab6e-723efa8f8926 · outbound
This paper cites Optimizing fpga-based accelerator design for deep convolutional neural networks,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Optimizing fpga-based accelerator design for deep convolutional neural networks,
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.602020Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c46846ef-296d-4cec-a985-eb657b08d346 · outbound
This paper cites Fast convolutional neural networks on fpgas with hls4ml,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Fast convolutional neural networks on fpgas with hls4ml,
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.607271Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cbfb14a-e5c6-4747-bb39-4214dbf047a0 · outbound
This paper cites Fpga/dnn co-design: An efficient design methodology for iot intelligence on the edge,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Fpga/dnn co-design: An efficient design methodology for iot intelligence on the edge,
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.612027Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 084e75d0-255f-4078-86b5-ee3259421a66 · outbound
This paper cites Scalehls: a scalable high-level synthesis framework with multi-level transformations and optimizations: invited,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Scalehls: a scalable high-level synthesis framework with multi-level transformations and optimizations: invited,
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.619271Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2da0ad38-684c-46d7-8d7c-23877b16583d · outbound
This paper cites Deep residual learning for image recognition,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Deep residual learning for image recognition,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.622161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5548c231-1f7f-418e-82e6-8dfb81a96958 · outbound
This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.628854Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c5c555a-8cd5-4a13-9b81-b6db0ea1d6ae · outbound
This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.634065Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9a1cb994-d205-4c14-9c30-1d9bcb5e4e43 · outbound
This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.639680Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fd7150c-bf7c-43c0-9b97-72f7a5cf568b · outbound
This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools MobileNetV2: Inverted Residuals and Linear Bottlenecks
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.644960Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f24dbd40-6696-4d10-9e6d-2364b4492660 · outbound
This paper cites Searching for MobileNetV3.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Searching for MobileNetV3
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.650469Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dab2105b-999b-413b-a62a-0a7a3b1d4cd5 · outbound
This paper cites Mistral 7B.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Mistral 7B
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.656017Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f4ff5bde-cfcb-4532-b672-4ddc02678ccb · outbound
This paper cites Gemma: Open Models Based on Gemini Research and Technology.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Gemma: Open Models Based on Gemini Research and Technology
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.661298Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 095ebf17-7c3a-410d-a4f8-9c4491eb28ad · outbound
This paper cites Autodse: Enabling software programmers to design efficient fpga accelerators,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Autodse: Enabling software programmers to design efficient fpga accelerators,
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.666141Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a3ec27ac-f403-4fc7-992f-2473d4eb2f48 · outbound
This paper cites Hlsfactory: A framework empowering high-level synthesis datasets for machine learning and beyond,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Hlsfactory: A framework empowering high-level synthesis datasets for machine learning and beyond,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:34:27.597504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5aa84fdf-e4db-4327-b262-df770e48a4b4 · outbound
This paper cites SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.678692Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e81ce819-c098-4308-9cea-e6c403a22185 · outbound
This paper cites Gemma 2: Improving Open Language Models at a Practical Size.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Gemma 2: Improving Open Language Models at a Practical Size
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.691689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e208c05f-fcd9-4ad1-babd-562f36e5412e · outbound
This paper cites Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.698505Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8cf2f221-e91f-4232-bd00-a6f29444b514 · outbound
This paper cites babble: Learning better abstractions with e-graphs and anti-unification,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools babble: Learning better abstractions with e-graphs and anti-unification,
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.703103Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a83c2676-21fc-48b2-b1a7-9e4c0d9b255c · outbound
This paper cites Rover: Rtl optimization via verified e-graph rewriting,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Rover: Rtl optimization via verified e-graph rewriting,
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.707221Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d3bfae9-ba55-4bce-a6fd-c09dded427f0 · outbound
This paper cites Seer: Super-optimization explorer for high-level synthesis using e-graph rewriting,.
ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools Seer: Super-optimization explorer for high-level synthesis using e-graph rewriting,
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:34:26.715832Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation f4be0b60-0a9e-49b5-8bb3-fc0b3ee9a027 · inbound
Shift-Left High-Level Synthesis Verification via Knowledge-Augmented LLM Agent cites this paper.
Shift-Left High-Level Synthesis Verification via Knowledge-Augmented LLM Agent ForgeBench: A Machine Learning Benchmark Suite and Auto-Generation Framework for Next-Generation HLS Tools
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T18:28:49.786656Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.