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Paper Citation Record · LEDGER

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

As of 8 August 2026, this Paper Citation Record lists 96 of 96 outbound references and 7 inbound Pith citation observations for arXiv:2505.22086.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.22086 v2

Coverage vector

measured 96 of 96 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:21:00.485955Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:10:51.240592Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T07:57:45.331962Z

Reference resolution

96 of 96 outbound references displayed

  • verified exact4
  • verified fuzzy61
  • unresolved31
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b00bb0c-b9df-4e1d-b47b-4008d7e84e3a · outbound

This paper cites Jouppi, Doe Hyun Yoon, Matthew Ashcraft, Mark Gottscho, Thomas B.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Jouppi, Doe Hyun Yoon, Matthew Ashcraft, Mark Gottscho, Thomas B

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:47.947967Z digest=sha256:a8d3ba0d8526534a1e835306571e3ab71f15900e890125695e7b8e7d65f08160

Observation e531cfa7-c96d-40d4-9ee9-362620c3c380 · outbound

This paper cites Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Borchers, et al.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Jouppi, Cliff Young, Nishant Patil, David Patterson, Gaurav Agrawal, Raminder Bajwa, Sarah Bates, Suresh Bhatia, Nan Boden, Borchers, et al

Reference 2

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no resolver link, observed 2026-08-07T13:20:48.002149Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.002149Z digest=sha256:05cbc78ac956acfb52f7844db80536d73c59257afd18c0584b1f10a073f56580

Observation c92cce96-27b9-444b-86ab-08f7ef526092 · outbound

This paper cites Emer, and Vivienne Sze.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Emer, and Vivienne Sze

Reference 3

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no resolver link, observed 2026-08-07T13:20:48.118621Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.118621Z digest=sha256:3a7a4407ca12a37cd19f6e7c13093f956e852f124348006d4a52cbea2a8f5cca

Observation 6f8738d5-5e9d-4c90-9257-61db7044a128 · outbound

This paper cites an unresolved cited work.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Unresolved cited work

Reference 4

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no resolver link, observed 2026-08-07T13:20:48.240819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.240819Z digest=sha256:58a6512464553237085b1ebceec3fb742ed1ad0755b461df9bd6cd1988205d58

Observation 46a564ef-4140-47cf-a0ff-b2cf479e7e13 · outbound

This paper cites Fusion-3D: Integrated acceleration for instant 3D reconstruction and real-time rendering.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Fusion-3D: Integrated acceleration for instant 3D reconstruction and real-time rendering

Reference 5

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no resolver link, observed 2026-08-07T13:20:48.356691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.356691Z digest=sha256:420cf77ba9682c6decb547218cb0dcda989ef10a92577e22021dc337848a1707

Observation 8b3b73f1-0474-4c06-a1ce-723353827620 · outbound

This paper cites CamPU: A multi-camera processing unit for deep learning- based 3D spatial computing systems.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs CamPU: A multi-camera processing unit for deep learning- based 3D spatial computing systems

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:48.479135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.479135Z digest=sha256:877cefc6b696e55088c4ee5733a1b3c942f59b4b67ff02f26d9dc61fec7e7f87

Observation 77d82bb7-3ddb-4095-94ae-d76b7a7899ee · outbound

This paper cites Neuman, Radhika Ghosal, Thomas Bourgeat, Brian Plancher, and Vijay Janapa Reddi.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Neuman, Radhika Ghosal, Thomas Bourgeat, Brian Plancher, and Vijay Janapa Reddi

Reference 7

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no resolver link, observed 2026-08-07T13:20:48.700158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.700158Z digest=sha256:2766602b1422bfae14c40cd49176459c7a52f3524dcdd2f1b0209a97aaf3de7d

Observation 9489f8c2-3964-44d6-b248-b99a97e827ce · outbound

This paper cites Neuman, Brian Plancher, Thomas Bourgeat, Thierry Tambe, Srinivas Devadas, and Vijay Janapa Reddi.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Neuman, Brian Plancher, Thomas Bourgeat, Thierry Tambe, Srinivas Devadas, and Vijay Janapa Reddi

Reference 8

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no resolver link, observed 2026-08-07T13:20:48.809350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.809350Z digest=sha256:5fc5877667c001142c3d04892b7571d4a1676d96a4cfddadab0702862677c495

Observation 8531a82d-0931-4571-9c17-7e485e58f605 · outbound

This paper cites BLESS: Bandwidth and locality enhanced smem seeding acceleration for DNA sequencing.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs BLESS: Bandwidth and locality enhanced smem seeding acceleration for DNA sequencing

Reference 9

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unresolved
no resolver link, observed 2026-08-07T13:20:48.954569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:48.954569Z digest=sha256:4155bf852074739cc0f63b869fc3e96e4e13bbb47add73096fa0d7d1f694ca56

Observation a39ef9cd-e9ba-4067-b2da-c22e62cf83f7 · outbound

This paper cites QUETZAL: Vector acceleration framework for modern genome sequence analysis algorithms.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs QUETZAL: Vector acceleration framework for modern genome sequence analysis algorithms

Reference 10

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no resolver link, observed 2026-08-07T13:20:49.093773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.093773Z digest=sha256:fdcfc29ec6967e7c5fc5634cd76002e3af8a5e74baab5e8364609a6fd82b2048

Observation be58dcd0-db5f-458d-8ee6-614184d76680 · outbound

This paper cites GMX: Instruction set extensions for fast, scalable, and efficient genome sequence alignment.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs GMX: Instruction set extensions for fast, scalable, and efficient genome sequence alignment

Reference 11

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no resolver link, observed 2026-08-07T13:20:49.216922Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.216922Z digest=sha256:8538cd448d988d3ea598f1392ed7802e84cb0d43789893112904239883c20aee

Observation e8b4be52-eb10-42cb-9e71-b133b5442167 · outbound

This paper cites Kalsi, Ziyi Zuo, Can Firtina, Meryem Banu Cavlak, Jeremie Kim, Nika Mansouri Ghiasi, Singh, et al.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Kalsi, Ziyi Zuo, Can Firtina, Meryem Banu Cavlak, Jeremie Kim, Nika Mansouri Ghiasi, Singh, et al

Reference 12

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no resolver link, observed 2026-08-07T13:20:49.321080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.321080Z digest=sha256:036f0e910a0662e6a0b4e87e2ff8516db990980bc76ae338a1f8df0e55beb0de

Observation 29bdd0e8-7647-498e-8c8c-fd93ddbccc82 · outbound

This paper cites Amant, Karthikeyan Sankaralingam, and Doug Burger.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Amant, Karthikeyan Sankaralingam, and Doug Burger

Reference 13

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unresolved
no resolver link, observed 2026-08-07T13:20:49.432408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.432408Z digest=sha256:abc11965fbbc413d0e85f83326cffa9c6621d7c12cd3c866f4df737b3fabfcb2

Observation a999a40a-14f5-43e7-b59f-77466830e8cf · outbound

This paper cites Democratizing domain-specific computing.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Democratizing domain-specific computing

Reference 14

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unresolved
no resolver link, observed 2026-08-07T13:20:49.602736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.602736Z digest=sha256:89d745ba5a1e811e82e89e682005068a81da7a12afe75f9444922a0f858667b4

Observation 466c065c-e956-41d9-86ed-60619661c0b2 · outbound

This paper cites High-Level Synthesis for FPGAs: From prototyping to deployment.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs High-Level Synthesis for FPGAs: From prototyping to deployment

Reference 15

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no resolver link, observed 2026-08-07T13:20:49.754312Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.754312Z digest=sha256:5a588d47e27e1954ef05b0f5191e8bc3e046314aaec9789c838227bdd89ac61c

Observation e27a9c9d-fa23-4659-bae6-6d535e38bf45 · outbound

This paper cites FPGA HLS today: Successes, challenges, and opportunities.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs FPGA HLS today: Successes, challenges, and opportunities

Reference 16

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no resolver link, observed 2026-08-07T13:20:49.942359Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:49.942359Z digest=sha256:7b437854136d8b1eb5e69bd225d3bffbd2ce4ec699ee3a4a53fb401de0b4372f

Observation d4e9bf40-4248-4a29-b4b6-4b26ad12cc8d · outbound

This paper cites Adaptive simulated annealer for high level synthesis design space exploration.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Adaptive simulated annealer for high level synthesis design space exploration

Reference 17

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:13.407880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.107882Z digest=sha256:6579651e5eeae1c17c53c52617f4a35d8fe3ec648c4584557f4d39af63b2a137

Observation f4a68057-bcdc-4838-8470-e816e0d83c56 · outbound

This paper cites Parallel high-level synthesis design space exploration for behav- ioral IPs of exact latencies.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Parallel high-level synthesis design space exploration for behav- ioral IPs of exact latencies

Reference 18

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:13.259142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.202029Z digest=sha256:ae481fb917cdab4884f5e9759fe589ac65a38ed44bf02cecd5fd362252687f2e

Observation 3f360231-2618-45a4-848a-2d48eda352be · outbound

This paper cites Probabilistic multiknob high-level synthesis design space exploration acceleration.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Probabilistic multiknob high-level synthesis design space exploration acceleration

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:13.069682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.252562Z digest=sha256:c283cf788dc5b0ab5297b15d22f3acf05c5dfa55059b4f753082c7e8396d4c66

Observation a34607f4-869f-467a-af6b-658fddbad3d4 · outbound

This paper cites Correlated multi-objective multi-fidelity optimization for HLS directives design.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Correlated multi-objective multi-fidelity optimization for HLS directives design

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:12.912183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.306255Z digest=sha256:727e96d92bd615b6e14c49c6aa92f102ea4d61a747d7f534af5742ab91bdbaf0

Observation 8f2a4197-5ebe-4300-9112-f55ab7721cf8 · outbound

This paper cites Lattice-traversing design space explo- ration for high level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Lattice-traversing design space explo- ration for high level synthesis

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:12.674858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.386259Z digest=sha256:94407c6e624933de110c88ebf566172d20ba0845cb74b3bf8cbdeb68d7a5feda

Observation 23ab54f9-b09b-436d-a553-197e6660d998 · outbound

This paper cites S2FA: An accelerator automation framework for heterogeneous computing in datacenters.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs S2FA: An accelerator automation framework for heterogeneous computing in datacenters

Reference 22

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raw_fallback, observed 2026-08-07T13:21:12.508712Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.511053Z digest=sha256:655a3d39eadb886f1ab2cf60b831926c75aec20606e78e76beba8a87683f86ac

Observation 0d17e399-5cf7-4840-a363-1d14b3245913 · outbound

This paper cites Towards a comprehensive benchmark for high-level synthesis targeted to FPGAs.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Towards a comprehensive benchmark for high-level synthesis targeted to FPGAs

Reference 23

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raw_fallback, observed 2026-08-07T13:21:12.333557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.581225Z digest=sha256:392c34d4dd97ab8e4a6c667f7458efb9b2469184344453d14deaa31fa998b72a

Observation ed8548c4-da5b-49c6-bfc5-976b6b71b317 · outbound

This paper cites Automated accelerator optimization aided by graph neural networks.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Automated accelerator optimization aided by graph neural networks

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:12.141005Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.709478Z digest=sha256:b28e4e6d8662d603371b8977c6d0b841f7226ab643d61ea591e94ddf7ac6b68b

Observation 4ef37abe-88e3-42e6-bd8a-b4aa7faf1577 · outbound

This paper cites Robust GNN-Based representation learning for HLS.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Robust GNN-Based representation learning for HLS

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.962397Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.790301Z digest=sha256:3818bc9a39271cd816411a2111420f65b4efa4954230e42021d82f4f39a1218e

Observation 08bdf5c2-3955-4a0e-bce9-434adbf44e8b · outbound

This paper cites IronMan-Pro: Multiobjective design space exploration in HLS via reinforcement learning and graph neural network-based modeling.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs IronMan-Pro: Multiobjective design space exploration in HLS via reinforcement learning and graph neural network-based modeling

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.794547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.889326Z digest=sha256:e1f7da0c0e2c6ed366eaebb35eaa7992251170e2e2a6adb3cf0a95137a33f17a

Observation db013fe0-57a9-4dbb-b87d-81f2a1fa4655 · outbound

This paper cites COMBA: A comprehensive model-based analysis framework for high level synthesis of real applications.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs COMBA: A comprehensive model-based analysis framework for high level synthesis of real applications

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.589704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:50.963468Z digest=sha256:ffaf3d46e3090ba3bd001d2374dcd8c2f4a6e0dc348a12988f5231a5c3a90d99

Observation 12ff1c2b-e7bf-4b0b-b6c9-c7a7a917f857 · outbound

This paper cites Lin-Analyzer: A high- level performance analysis tool for FPGA-based accelerators.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Lin-Analyzer: A high- level performance analysis tool for FPGA-based accelerators

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.425547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.032492Z digest=sha256:f27e385aa5c36ea1645aa2afe4e5c3024cc0a199d35e31a07ed03af9c8683815

Observation 0e353c90-79cc-4385-a7b4-4bc526c55408 · outbound

This paper cites Graph neural networks for high-level synthesis design space exploration.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Graph neural networks for high-level synthesis design space exploration

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.294033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.210499Z digest=sha256:3423d70ae6777b8590f9fb9197c2b988e4b5807a5adb81a79116050aa25d672c

Observation f4aa97dc-ff18-4fa8-8e60-4233de8ae60a · outbound

This paper cites Learning to compare hardware designs for high- level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Learning to compare hardware designs for high- level synthesis

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:11.137792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.366425Z digest=sha256:cee348d3350a799f7b4ceff54b843d571697ac77e1f3dff5716b926784788ebc

Observation cd627977-97fa-485e-a85c-5ce56c6df490 · outbound

This paper cites HGBO-DSE: Hierarchical gnn and bayesian optimization based hls design space exploration.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs HGBO-DSE: Hierarchical gnn and bayesian optimization based hls design space exploration

Reference 31

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raw_fallback, observed 2026-08-07T13:21:10.948695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.481107Z digest=sha256:f149bda68155480625342a4dd5c6184a42b6784d9fbe27f5976644f6c00c4232

Observation ad43ab5a-c6b8-4c9b-9402-677750c4701b · outbound

This paper cites ChatCPU: An agile CPU design and verification platform with LLM.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs ChatCPU: An agile CPU design and verification platform with LLM

Reference 32

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raw_fallback, observed 2026-08-07T13:21:10.764679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.600520Z digest=sha256:04f8c684b03792b4f5c938c58127e3d457bd38ba9a39008b62edbb2d168e0131

Observation 0435330c-f043-477e-995e-9cda9d58906a · outbound

This paper cites MEIC: Re-thinking RTL debug automation using LLMs.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs MEIC: Re-thinking RTL debug automation using LLMs

Reference 33

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raw_fallback, observed 2026-08-07T13:21:10.580300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.721781Z digest=sha256:1724b7f7f3668f5ad7517e411b5ad4f9774f41701a15e471cc0765abb5e4ea0e

Observation e894bc90-cfc9-4820-94fc-23b1216ea524 · outbound

This paper cites ChatEDA: A large language model powered autonomous agent for EDA.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs ChatEDA: A large language model powered autonomous agent for EDA

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:10.346543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.839492Z digest=sha256:06d0e7129449136a019c160162a8a3de266eb07ee59d878b2ea7c55ae4c7b81a

Observation 69bc03c7-bf65-4ba4-a1c7-9b47791ff480 · outbound

This paper cites RTLFixer: Automatically fixing RTL syntax errors with large language model.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs RTLFixer: Automatically fixing RTL syntax errors with large language model

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:10.157630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:51.937735Z digest=sha256:c44e5dd0cd9351333b62d5641c225ce52717846ab7e28b9643d92a46a0ea3a83

Observation 7529ffae-b5cc-4bd5-904d-8e16b6e42bc2 · outbound

This paper cites GPT4AIGChip: Towards next-generation AI accelerator design automation via large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs GPT4AIGChip: Towards next-generation AI accelerator design automation via large language models

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.940309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.010958Z digest=sha256:7f30bd2fddfea67ea395d5aca3c9ad6db239cd3ed15f43592bacfefc2783e3e3

Observation d413918c-41de-4853-a9c6-4c20f46a51b1 · outbound

This paper cites Large Language Models as Optimizers.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Large Language Models as Optimizers

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:52.089259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:52.089259Z digest=sha256:9b5dd841998d90471671757dd96eb3cab528e773a837fe15c13cedb5e9a319bd

Observation dfd36066-0e11-4808-80b1-5dee5a24f4a6 · outbound

This paper cites Large language models as evolutionary optimizers.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Large language models as evolutionary optimizers

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.831938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.190020Z digest=sha256:add0e77bc1ccc44d21ef58edbe6a5f4c05e02c503c44f0bfb64ff364b39d0795

Observation 71b0cbff-f8d6-4a13-aaee-826a1c96dee0 · outbound

This paper cites Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:52.314623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:52.314623Z digest=sha256:bf89f839e3293f743210aa39fe02a712eb243524badcc828140d925dc989294d

Observation ee27183c-98e1-4908-819b-96752c7e44f1 · outbound

This paper cites Large Language Models to Enhance Bayesian Optimization.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Large Language Models to Enhance Bayesian Optimization

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:52.389693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:52.389693Z digest=sha256:b7972f6258baa64b509ce0cb74c0b79ee71d0f489510ff35140c118f76227047

Observation 01d48144-5e0a-44d9-95c1-195cede54ce8 · outbound

This paper cites Evolutionary com- putation in the era of large language model: Survey and roadmap.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Evolutionary com- putation in the era of large language model: Survey and roadmap

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.677256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.496604Z digest=sha256:ca9735633b98caae892641a0263a640ac47ad46ab77ce6ab7f1be8c78b6b1342

Observation 7a9d2e82-6246-4171-8cf4-d6c92ac34fef · outbound

This paper cites Efficient task transfer for HLS DSE.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Efficient task transfer for HLS DSE

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.596054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.604160Z digest=sha256:1c3c354e9a4bac927310c3736b602ec7f73bb1aa7d86f5163a3185ffd69ec53b

Observation 731e7f9a-458a-4816-a7bd-da4269c59ccb · outbound

This paper cites AutoDSE: Enabling software programmers to design efficient FPGA accelerators.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs AutoDSE: Enabling software programmers to design efficient FPGA accelerators

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.466231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.733136Z digest=sha256:10b38b1a6bcbd24856df4be57f3e70934a0e1d191dc0e2a7a9a34cc7acd53ace

Observation c005ea1e-0699-4c81-911f-3ff8239c3534 · outbound

This paper cites Design space exploration of multiple loops on fpgas using high level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Design space exploration of multiple loops on fpgas using high level synthesis

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.291128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.836382Z digest=sha256:7c5de40012d60e784d81ffa28aa75c2bc155517f8bcffbba57a43eb396aeefe8

Observation 226865ed-1b55-48b2-befb-ceeac3a8b3c8 · outbound

This paper cites Exploiting loop-array dependencies to accelerate the design space exploration with high level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Exploiting loop-array dependencies to accelerate the design space exploration with high level synthesis

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.194557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:52.950800Z digest=sha256:7698a9613e360546553b5d91cb399272a30c3504dc86f187b1d9aa63867fd2ab

Observation 74b13955-b23e-4f79-aa63-210877c3c352 · outbound

This paper cites A unified framework for automated code transformation and pragma insertion.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs A unified framework for automated code transformation and pragma insertion

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:09.008774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:53.090759Z digest=sha256:f3268697c2a544f512480a9f7ff6cedb81a68ed2fe771584acfc8cd7f94ac84e

Observation fe8f6b75-4c14-4db0-98d9-a4c74e815a7c · outbound

This paper cites Automatic hardware pragma insertion in high-level synthesis: A non-linear programming approach.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Automatic hardware pragma insertion in high-level synthesis: A non-linear programming approach

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:08.863424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:53.273199Z digest=sha256:b6235d1fe90d1358dd0c2502a31a0895b276cdc3df43e86c0ebf4a0443ea9ba9

Observation 6e7ec4b2-1de1-4fe4-aa62-0e48cd033533 · outbound

This paper cites High-level synthesis performance prediction using GNNs: benchmarking, modeling, and advancing.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs High-level synthesis performance prediction using GNNs: benchmarking, modeling, and advancing

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:08.655550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:53.453418Z digest=sha256:1593788253bdc2ec8403e5e858d099bcf9c6ac75e3c590e4297aa1ef1e50f9a8

Observation 0e1f8dd5-7a85-4661-b1ad-8f3dfb3e23ea · outbound

This paper cites LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:53.613548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:53.613548Z digest=sha256:69bd50220fe1af05a2545b98666b4f4a30d7e96d558f0a4051e847e4d8694cc0

Observation 80f9c058-b68a-4b6a-9a94-cb368239ac6e · outbound

This paper cites Betterv: controlled verilog generation with discriminative guidance.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Betterv: controlled verilog generation with discriminative guidance

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:08.416950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:53.733702Z digest=sha256:97f695c7d701547a83b23d7588de20bd75f9e7f0fd1477e03b75fd76ad5b17fc

Observation 1f49d08a-d38e-4467-93f8-316aca9d1af9 · outbound

This paper cites Location is Key: Leveraging Large Language Model for Functional Bug Localization in Verilog.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Location is Key: Leveraging Large Language Model for Functional Bug Localization in Verilog

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:53.884829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:53.884829Z digest=sha256:65fd57d88b0ad3a9e6fff68e4a88af85ea9088944dbb96355708d8f8d0b97096

Observation 4814d0dd-40e7-4b4c-aaaf-bd95d274d4c9 · outbound

This paper cites UVLLM: An Automated Universal RTL Verification Framework using LLMs.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs UVLLM: An Automated Universal RTL Verification Framework using LLMs

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:54.004393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:54.004393Z digest=sha256:07e77474277bfbc670ea01075aacc9469ec0d4f250721477c97d17c95c12212d

Observation 117a65bd-cc1b-496a-b4c1-50fcdb678ea1 · outbound

This paper cites VGV: Verilog generation using visual capabilities of multi-modal large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs VGV: Verilog generation using visual capabilities of multi-modal large language models

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:08.267872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:54.167501Z digest=sha256:306e1596065ea0f78f9315c59dd14407f4f471c441fa5259b982d7cfc79f5789

Observation e10e45f6-44c4-4cc0-9581-4e934c2ab260 · outbound

This paper cites VeriGen: A large language model for verilog code gen- eration.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs VeriGen: A large language model for verilog code gen- eration

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:08.056152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:54.326813Z digest=sha256:4731c4eb5805a00fd4632c8b29c81649d933414d1a9dc4c242e6dfd0b445f1cf

Observation a3a32fe1-c24d-49e5-b512-54752dcc952b · outbound

This paper cites ADO-LLM: Analog design bayesian optimiza- tion with in-context learning of large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs ADO-LLM: Analog design bayesian optimiza- tion with in-context learning of large language models

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.929277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:54.436147Z digest=sha256:2cf7f9df86c5f339af7d2f3124e71e5ad046fa87cc68dbc050eb770dbc6d3b34

Observation 868f9fd2-ebd7-4216-a188-267a11d638ee · outbound

This paper cites LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LEDRO: LLM-Enhanced Design Space Reduction and Optimization for Analog Circuits

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:54.609432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:54.609432Z digest=sha256:d2fb53aec9ef8d9d0d2f802caf9a6bf80ac734845e5fab43f188d8c0ed867960

Observation af6188d9-7e3b-4024-8183-14dbc35767fe · outbound

This paper cites VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:54.735772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:54.735772Z digest=sha256:40e48163b492f5aaf1ffebeb085cf8f8dd439ae0f97a975833d3bcdab11d71fa

Observation 3ec5f2a1-0732-431b-80ce-7f6d64f9296d · outbound

This paper cites Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback

Reference 58

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:21:01.949937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:54.929448Z digest=sha256:0f970bd58127a5dd9c494017eba31463ce030a31efd74675cb3ab2d5276c4985

Observation e5835a3e-9846-4754-8c38-6499364cae7e · outbound

This paper cites Automated C/C++ program repair for high-level synthesis via large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Automated C/C++ program repair for high-level synthesis via large language models

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.739547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:55.090496Z digest=sha256:c3674e0f96e0b371117b3a526f83855d0388cd11f249f4088bd369a64639746b

Observation 04fed88b-5acc-452f-abfe-6bb3ac6c0ea3 · outbound

This paper cites HLSPilot: LLM-based high-level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs HLSPilot: LLM-based high-level synthesis

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.618613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:55.227702Z digest=sha256:f3b8b83b934bc085ffb6c1272e80316bc4c4469a650c6c7e23f2f4dea0e50957

Observation af081f9c-dcbd-4126-b123-b43fb8dcaefe · outbound

This paper cites Optimizing high-level synthesis designs with retrieval-augmented large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Optimizing high-level synthesis designs with retrieval-augmented large language models

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.475326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:55.395176Z digest=sha256:dcccc777757b7c8a8fc849048d0633cd4ed9b2b27dc26f4021cec5838c9da5b9

Observation ebf9db77-c891-490c-9503-24e0545ee33a · outbound

This paper cites LIFT: LLM-Based Pragma Insertion for HLS via GNN Supervised Fine-Tuning.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LIFT: LLM-Based Pragma Insertion for HLS via GNN Supervised Fine-Tuning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:55.528840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:55.528840Z digest=sha256:18cbc8c78c60c02e9ece924c64346ab831c4920f12d73e2c08feef393aa63941

Observation fa46d5bb-e32f-4162-a90d-34ce91e17793 · outbound

This paper cites LLM-DSE: Searching accelerator parameters with LLM agents.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LLM-DSE: Searching accelerator parameters with LLM agents

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:55.692893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:55.692893Z digest=sha256:3ff2caed3d87ddbd6414ec8eaa2404e96264bceacedb0a61c41a494f822055fe

Observation e7602a98-4ddf-49a0-a423-e485b1bc0141 · outbound

This paper cites C2HLSC: Leveraging Large Language Models to Bridge the Software-to-Hardware Design Gap.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs C2HLSC: Leveraging Large Language Models to Bridge the Software-to-Hardware Design Gap

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:21:01.501987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:55.826613Z digest=sha256:721768f2c77e0e356a9e77f93cc50f59e41f62f1d032567ed46a60cfeccd53dd

Observation 01f73713-b557-4719-8eb9-c92a2386cf06 · outbound

This paper cites Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:55.947884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:55.947884Z digest=sha256:d2229fcb3b8b0d8f74bb265318bd7d2a8689e15f312534609d12f7dbbaec3c15

Observation fe9b039c-7aee-48c6-bd4d-62cc5476fc4d · outbound

This paper cites Pareto multi-task learning.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Pareto multi-task learning

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.319056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.056136Z digest=sha256:5042857a7643665a7a150bc0bf589442716f8d42c7cc0564873f3c0bd5b82d87

Observation bcba8da1-4357-44ed-8f43-ad0ee3cc90ed · outbound

This paper cites Profiling pareto front with multi-objective stein variational gradient descent.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Profiling pareto front with multi-objective stein variational gradient descent

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:07.156111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.211308Z digest=sha256:8f2428942b7497e3dbba1acacd59d883bf29a45864e190504d92d3cee53ffb03

Observation ea7cf99d-c604-4b86-bf21-0f405a527719 · outbound

This paper cites MOEA/D: A multiobjective evolutionary algorithm based on decomposition.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs MOEA/D: A multiobjective evolutionary algorithm based on decomposition

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:06.950765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.381282Z digest=sha256:84f10f5d280c1b388367764342748e6e81637caeab529864f76632a6bfbb797a

Observation ef6351a8-5db1-46bf-8422-fe02bb521426 · outbound

This paper cites Learning the pareto front with hypernetworks.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Learning the pareto front with hypernetworks

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:06.787703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.553183Z digest=sha256:84873637a307675f3960685f7193f77ef4780fbd6a696fd88b3f0f2640821d34

Observation 612a6806-b7c2-4b3c-acc5-5d10561b57f0 · outbound

This paper cites Pareto set learning for expensive multi-objective optimization.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Pareto set learning for expensive multi-objective optimization

Reference 70

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verified fuzzy
raw_fallback, observed 2026-08-07T13:21:06.607352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.669884Z digest=sha256:85a0c6dd700586b581b5734de43591f8c1190afb9a0e878d861027beaf660cc7

Observation e3c22013-f006-472c-a595-5ef0d4bf3d55 · outbound

This paper cites Hypervolume maximization: a geometric view of pareto set learning.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Hypervolume maximization: a geometric view of pareto set learning

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:06.303536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.866854Z digest=sha256:24d03a9a31e2ce5501c214638792343ff6dacac7097541babb3f9e2f41ed20f6

Observation b668802c-cf42-495a-b78d-d6ceb6b7a301 · outbound

This paper cites Panacea: Pareto alignment via preference adaptation for LLMs.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Panacea: Pareto alignment via preference adaptation for LLMs

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:06.050900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:56.990525Z digest=sha256:9a95a08034c69a065c268c9c6462c78be82a57890af14083387f83296b8fb163

Observation 6eb13439-dd62-434b-b665-cc954a9d1277 · outbound

This paper cites Parrot: Pareto-optimal multi-reward reinforcement learning framework for text-to-image generation.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Parrot: Pareto-optimal multi-reward reinforcement learning framework for text-to-image generation

Reference 73

Resolution
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raw_fallback, observed 2026-08-07T13:21:05.872218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:57.138682Z digest=sha256:a7b02c843455c6104f7670c249f9989b5416c70f3fad954ab3dc994c353654dc

Observation 47b90f77-32f7-45ec-bb05-4380562e211b · outbound

This paper cites Evolution of heuristics: towards efficient automatic algorithm design using large language model.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Evolution of heuristics: towards efficient automatic algorithm design using large language model

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:05.613000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:57.264014Z digest=sha256:71356d7fb253e6c0066b104a4815457340fbe414ca3d2386c8488400c3b84068

Observation bc523f9b-13c4-4f49-847c-bcffcb9954f0 · outbound

This paper cites Mathematical discoveries from program search with large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Mathematical discoveries from program search with large language models

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:57.435820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:57.435820Z digest=sha256:df9817518ce77e272dbca3dcec45a0577ac95d3ff101655a2620d352fb05cc84

Observation 1b0e85c0-69ea-468d-908e-0cb4c2e20320 · outbound

This paper cites Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:57.564365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:57.564365Z digest=sha256:1d6f89fb8ade9db7461a938ca4aa90ad4054d9d27938d627a60e918e33a19376

Observation b29d4414-931d-4999-a9d9-254677e0fbb5 · outbound

This paper cites Multi-objective evolution of heuristic using large language model.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Multi-objective evolution of heuristic using large language model

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:05.357916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:57.715958Z digest=sha256:b5a63489b106469f3d7c35a47bba8fa5daa4782ec4ebed4d321524730b686bd0

Observation 8133cfa4-f097-44d0-ab6f-79d0c38088ed · outbound

This paper cites ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:57.836152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:57.836152Z digest=sha256:58887ffb1051affcf2a7179cae6fc3e55e9a52c20d2b0716788ca8fe77e1c3d9

Observation ecd02f77-7398-4a64-8761-9780b960167a · outbound

This paper cites EvoPrompting: Language models for code-level neural architecture search.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs EvoPrompting: Language models for code-level neural architecture search

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:05.176345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:57.965395Z digest=sha256:4d08c3c9d4aac4d17b16389ade684304364a7763b8124ec9b063b997fb34b48f

Observation f594e98b-0865-40b4-86fb-e326648d4098 · outbound

This paper cites GPT-NAS: Neural architecture search meets generative pre-trained transformer model.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs GPT-NAS: Neural architecture search meets generative pre-trained transformer model

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:05.000004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.108307Z digest=sha256:dd065c11b8f4c24942e457564bfcededd574daaee39869a94596066d200c6371

Observation 264bc2f9-f560-4ecc-a21c-d5520c0fc97f · outbound

This paper cites LLMatic: neural architecture search via large language models and quality diversity optimization.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LLMatic: neural architecture search via large language models and quality diversity optimization

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:04.849837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.249904Z digest=sha256:46031fbc2ca638c4a175413fdbca5b4d088f9ea4d63d8cb8461b5a0861d18d8e

Observation a8fff4be-bea3-4af8-a2db-779facbce28d · outbound

This paper cites Graph neural architecture search with gpt-4.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Graph neural architecture search with gpt-4

Reference 82

Resolution
verified exact
raw_fallback, observed 2026-08-07T13:21:01.199673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.422471Z digest=sha256:30976158032f04517f6e52fbf83ea999054b72530bd7017585fc8299d9adcf17

Observation 8efb14b5-9d6c-4877-996f-b62112613061 · outbound

This paper cites LLM guided evolution-the automation of models advancing models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs LLM guided evolution-the automation of models advancing models

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:04.701284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.523884Z digest=sha256:08c06665d2aa037d7f52029cee102e9810e5bb06bcc38b4bc87c99d7ee2a1d05

Observation 58322553-8939-4db5-b39b-2f72c889f0c8 · outbound

This paper cites Design principle transfer in neural architecture search via large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Design principle transfer in neural architecture search via large language models

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:04.551197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.679582Z digest=sha256:f7b2679e0f3868d51e7034dbf88b2c2403a4a8d0c01d9e1d2885cd337ad968a8

Observation 64c3c74a-2dc8-4dc3-8aa3-ea37377215e6 · outbound

This paper cites Intelligent4DSE: Optimiz- ing high-level synthesis design space exploration with graph neural networks and large language models.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Intelligent4DSE: Optimiz- ing high-level synthesis design space exploration with graph neural networks and large language models

Reference 85

Resolution
verified exact
raw_fallback, observed 2026-08-07T13:21:00.851616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:58.927233Z digest=sha256:cbfd228f29082a2e25c323944382c6b19dcfd4abe51a1163e6a0cce230f6b326

Observation 3c74167c-6c48-4b16-bc87-6b8763a49e4b · outbound

This paper cites High-level synthesis design space exploration: Past, present, and future.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs High-level synthesis design space exploration: Past, present, and future

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:04.447105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.101101Z digest=sha256:0a30a8832a52d3ed25c5df872926944c9b60b894ac7f09f2799518666be51793

Observation a449cc24-9f63-4f3d-98c8-7398bdb81e73 · outbound

This paper cites Carloni, and Laura Pozzi.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Carloni, and Laura Pozzi

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:04.191648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.308993Z digest=sha256:7d4d16dd851af1e3c0fe6deb23e7647fbbf8adfcca6fa341f8fa0a3cc84dc38c

Observation 702ce767-2b45-4777-b649-d0d9f901a3c8 · outbound

This paper cites CollectiveHLS: A collaborative approach to high-level synthesis design optimization.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs CollectiveHLS: A collaborative approach to high-level synthesis design optimization

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:03.861310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.423149Z digest=sha256:9b022d241f17df43b245e5c90415af73d034feefeeb1fbab522489bdfd055f82

Observation 5cc6378f-e147-46b1-a29d-815bc1a13fe7 · outbound

This paper cites an unresolved cited work.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Unresolved cited work

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-07T13:20:59.548289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:20:59.548289Z digest=sha256:257fd706c33d36daf2cd760e9827600601d1bb9132742956dbf703e8eb3d42a1

Observation 9c3bcde9-5801-4c5a-ac7d-6d616f57e990 · outbound

This paper cites PolyBench/C 4.2, 2016.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs PolyBench/C 4.2, 2016

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:03.598775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.655178Z digest=sha256:0e0d27b33a767cd60318f09c1269ffd675d6d6966800959485a4757cb4fc6f35

Observation 3c1b4a29-913c-44b8-b657-31e1141e8eb1 · outbound

This paper cites CHStone: A benchmark program suite for practical C-based high-level synthesis.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs CHStone: A benchmark program suite for practical C-based high-level synthesis

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:03.291018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.789768Z digest=sha256:3697f334f38320b973a5c59d8108a6b9c9e4b3002bd399d96eced61d2fb926b7

Observation bdcc097c-c187-4661-a93b-b61cc5377822 · outbound

This paper cites Mach- suite: Benchmarks for accelerator design and customized architectures.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Mach- suite: Benchmarks for accelerator design and customized architectures

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:03.139119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:20:59.906696Z digest=sha256:7419ee9f15a32eb22904b09fa49dbc02bcad791c7d0921df21753141e2c86770

Observation 1af6de2b-16e7-4d6b-b452-5c99881138ce · outbound

This paper cites Vitis High-Level Synthesis User Guide (UG1399), 2022.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs Vitis High-Level Synthesis User Guide (UG1399), 2022

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:03.017213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:21:00.052992Z digest=sha256:6e4ac4cd7f52d9d5b3be3b29ba351a9a30b7605caff119b1db6750efbdb9f80f

Observation e8b06a92-f28b-4125-bcf0-e92f93df159b · outbound

This paper cites off", "on.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs off", "on

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:02.912144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:21:00.209151Z digest=sha256:1dfa35c41b6b7ce51c8dafab98902f2443b8b155d8d07cf74cccb7821e9e8af0

Observation 5360bfc0-b27c-4c55-b452-851c5615ed98 · outbound

This paper cites – URL: https://github.com/hzkuang/HGBO-DSE • Lattice [21] – License: Available online.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs – URL: https://github.com/hzkuang/HGBO-DSE • Lattice [21] – License: Available online

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:02.651186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:21:00.332619Z digest=sha256:5ee02e51bd57cf218d8b62ca518eaade8f2e142e2f7b3fa8b331e33f2f96ab3a

Observation 37775b3f-7cad-4b91-8dc3-cf4e86efce29 · outbound

This paper cites – URL: http://polybench.sf.net.

iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs – URL: http://polybench.sf.net

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:21:02.354582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:21:00.485955Z digest=sha256:f9e00ac64d3f011fd4eefd599f633012c9db6f9783bfa7706ccfa775f357ba40

Pith citing papers

Observation 71ddfc0d-c3ee-43ea-97b0-2a05cde96190 · inbound

Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization? cites this paper.

Agent Factories for High Level Synthesis: How Far Can General-Purpose Coding Agents Go in Hardware Optimization? iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:28:23.476083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T00:25:47.186559Z digest=sha256:a85c5417e977b27e00d771b37044a8600d5c65d814b84ff6570791aa25edc87e

Observation 8d64ccd8-eee5-4060-a8f7-58b46fa4acd2 · inbound

Automated SVA Generation with LLMs cites this paper.

Automated SVA Generation with LLMs iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:06:00.688821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:14:26.057709Z digest=sha256:3f0b858c019cfd4a7cc6ecfdf1f85ef5d9b959ede23e1474287441ff1fde9312

Observation 0d8d36ff-83dc-44c3-b3dc-1ddc9f881670 · inbound

HYPERHEURIST: A Simulated Annealing-Based Control Framework for LLM-Driven Code Generation in Optimized Hardware Design cites this paper.

HYPERHEURIST: A Simulated Annealing-Based Control Framework for LLM-Driven Code Generation in Optimized Hardware Design iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:18:31.636700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T08:04:48.949697Z digest=sha256:73aa70d8650fe75fa6405b951e4b5f8c31244763054282b6fbd968bf99fd7029

Observation 2bd64dcb-bf05-4930-9f71-b5214a1a1a9c · inbound

RefEvo: Agentic Design with Co-Evolutionary Verification for Agile Reference Model Generation cites this paper.

RefEvo: Agentic Design with Co-Evolutionary Verification for Agile Reference Model Generation iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:11:14.576335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T03:16:00.089055Z digest=sha256:e2c2ad827f7ca7181c4440e0edcbd842acf5cc214ccb335504b55e461ff5e9b6

Observation 325cdcb4-55b9-49aa-a393-80342cf50408 · inbound

LLM-Driven Design Space Exploration of FPGA-based Accelerators cites this paper.

LLM-Driven Design Space Exploration of FPGA-based Accelerators iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:41:16.796233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T04:34:04.450499Z digest=sha256:8ecd943d12f5c0cdf36826c3ca6d510460cae03f85e146b64878304796f650b5

Observation 761ec280-4236-4c48-9964-dd1721814e70 · inbound

Towards Autonomous Accelerator Design: FPGA Accelerator Generation with SECDA cites this paper.

Towards Autonomous Accelerator Design: FPGA Accelerator Generation with SECDA iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-07-03T07:57:45.333548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T11:19:17.690153Z digest=sha256:8e3aa89f52c65044a71e0cef52d134483787039ba695c44f54b5f0f49d052252

Observation a7404c4a-af01-4e77-8db8-3f6d321319b3 · inbound

MicroEvo: Knowledge-Guided LLM Sampling for Efficient Microarchitecture Design Space Exploration cites this paper.

MicroEvo: Knowledge-Guided LLM Sampling for Efficient Microarchitecture Design Space Exploration iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T13:10:51.240592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:51.240592Z digest=sha256:ce8ca0f5b2c2519886ca6726d06b1eea93c13aa541142152c8ae9cb83041a0fc