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Paper Citation Record · LEDGER

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2607.17063.

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

pith.paper-citation-record.v1
2607.17063 v2

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T19:12:15.717303Z

measured 39 of 39 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b98b3750-40dd-4a51-9d2d-8f3fa57443ab · outbound

This paper cites Ieee standard for verilog register transfer level synthesis,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Ieee standard for verilog register transfer level synthesis,

Reference 1

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source=pdf_text observed=2026-08-01T19:12:11.230212Z digest=sha256:5b859eadc5282dd435f568650dcb5b45801fa9bdeeb4f85fc30fa854fd5df418

Observation 6b63dc67-d1f2-4ef7-91ef-c60c44cde0de · outbound

This paper cites Stack overflow is not dead yet: Crowd answers still matter,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Stack overflow is not dead yet: Crowd answers still matter,

Reference 2

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source=pdf_text observed=2026-08-01T19:12:11.342468Z digest=sha256:b173a124db67e8b008152a2afd27a758ec9f0fac43ae1756fec565d47b4221ed

Observation 3c3d6cac-d4c1-4acf-a67d-9694c1e6f4c3 · outbound

This paper cites Assessing and advancing benchmarks for evaluating large language models in software engineering tasks,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Assessing and advancing benchmarks for evaluating large language models in software engineering tasks,

Reference 3

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source=pdf_text observed=2026-08-01T19:12:11.467277Z digest=sha256:66b1be0ee3d8d43f05e00a3bd8124b144f6c8f30eb662ab48f6babd5aaaf5ed5

Observation 6d7e2512-e41b-488b-a711-8ca5d3bd6725 · outbound

This paper cites A survey of research in large language models for electronic design automation,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering A survey of research in large language models for electronic design automation,

Reference 4

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source=pdf_text observed=2026-08-01T19:12:11.583975Z digest=sha256:60995a1692183c8b899456f7dd2a0d0840659d96d109fc053c0db0f28fdfd098

Observation 6cf1972f-e7bd-4842-8b75-bfbb03c6f977 · outbound

This paper cites Verilogcoder: Autonomous verilog coding agents with graph-based planning and abstract syntax tree (ast)- based waveform tracing tool,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Verilogcoder: Autonomous verilog coding agents with graph-based planning and abstract syntax tree (ast)- based waveform tracing tool,

Reference 5

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source=pdf_text observed=2026-08-01T19:12:11.697197Z digest=sha256:cab23f662c5d9bf085f7235fdeec355fba135f27415c41bb062a9c69d1d5e62c

Observation a33ce13d-5394-4ca6-bf3a-33a83daf3dc9 · outbound

This paper cites Rtl- coder: Fully open-source and efficient llm-assisted rtl code generation technique,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Rtl- coder: Fully open-source and efficient llm-assisted rtl code generation technique,

Reference 6

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source=pdf_text observed=2026-08-01T19:12:11.864933Z digest=sha256:04ffe7e73c267f17318fe12e37505c5ecaa5c352a038023a47830e7904308ba2

Observation 589eacaf-2f97-4c7c-8147-a37178d1d4a5 · outbound

This paper cites Verilogeval: Evaluating large language models for verilog code generation,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Verilogeval: Evaluating large language models for verilog code generation,

Reference 7

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source=pdf_text observed=2026-08-01T19:12:11.986973Z digest=sha256:d12794e623af7da3ba6966d17df82289b8ef309bfd8404e0a054955bd7cf701c

Observation be8421ed-440f-4faf-ac3d-b95b5516020a · outbound

This paper cites Rtllm: An open-source benchmark for design rtl generation with large language model,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Rtllm: An open-source benchmark for design rtl generation with large language model,

Reference 8

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source=pdf_text observed=2026-08-01T19:12:12.103209Z digest=sha256:cf1d60145242dc3a450a9b4a06f2324308c9708bbcb9b396a26025089dcec823

Observation 0e77a384-fb53-4f9e-a422-c6dc15187a86 · outbound

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

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Betterv: controlled verilog generation with discriminative guidance,

Reference 9

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source=pdf_text observed=2026-08-01T19:12:12.195668Z digest=sha256:488e59c4881e9dbe4288838bc83d6e17de0318466f6950460e6ee7c4c827c4a6

Observation 32f48444-a091-43a7-84d3-5a292f5bd8f1 · outbound

This paper cites an unresolved cited work.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-01T19:12:12.311364Z digest=sha256:de925b064483e9e9955b98390f2ba1a64b7adb290a6a9215ba9bac2aea524f20

Observation 58745426-af49-4f75-952d-ffdb744fcdf6 · outbound

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

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automation

Reference 11

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source=pdf_text observed=2026-08-01T19:12:12.409804Z digest=sha256:95192d62d1de574602262efd9759e00f319ce2e2dcb0e9654f1d0d1b47df582d

Observation d364cbe7-286e-49f5-9312-260dbfbd2f05 · outbound

This paper cites Palnitkar,Verilog HDL: a guide to digital design and synthesis.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Palnitkar,Verilog HDL: a guide to digital design and synthesis

Reference 12

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source=pdf_text observed=2026-08-01T19:12:12.532353Z digest=sha256:893e79a7a67cc40fea63dad755e1aded898dec3bd54145b510663c56c23ca0c9

Observation 60bde134-9b76-4175-b495-fc9b77eff26d · outbound

This paper cites Ieee standard for verilog hardware description language,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Ieee standard for verilog hardware description language,

Reference 13

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source=pdf_text observed=2026-08-01T19:12:12.632230Z digest=sha256:d9014b1e9e8fd611631b873788a71f8bcf2981966f41c26de81180ae35f4b733

Observation c58722fc-6210-4076-b9be-b92971f4fdc7 · outbound

This paper cites Ieee standard for vhdl language reference manual,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Ieee standard for vhdl language reference manual,

Reference 14

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source=pdf_text observed=2026-08-01T19:12:12.747684Z digest=sha256:3e68ecda34eba4ef6fc99469d852afa6844a3ea6d742916f7411af51b7e2da95

Observation dbe223fd-e956-464d-80fa-c43f72be5abe · outbound

This paper cites Rtlfixer: Automatically fixing rtl syntax errors with large language models,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Rtlfixer: Automatically fixing rtl syntax errors with large language models,

Reference 15

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source=pdf_text observed=2026-08-01T19:12:12.809960Z digest=sha256:9f6ce71ad57d5c2d2f1e70be822433a1ab86f6aeeb5816df14b57536c0d3b29a

Observation f58a9b3e-94f1-4f82-b62a-a740e643aa92 · outbound

This paper cites Veridebug: A unified llm for verilog debugging via contrastive embed- ding and guided correction,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Veridebug: A unified llm for verilog debugging via contrastive embed- ding and guided correction,

Reference 16

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source=pdf_text observed=2026-08-01T19:12:12.864374Z digest=sha256:e8879c89cf218fe7cb715cd42a5876f94bbe1ec1cecfc72bc4e98a04779edcdc

Observation 91cf1a7d-3e77-496e-b616-9974b4617e9b · outbound

This paper cites Codev: Empowering llms with hdl generation through mul- tilevel summarization,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Codev: Empowering llms with hdl generation through mul- tilevel summarization,

Reference 17

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source=pdf_text observed=2026-08-01T19:12:12.957710Z digest=sha256:db2ff0af74aa387fd7a763023ef701b76e61ef80cd30524cb5930b030ea3a18f

Observation 1fed3c2a-b070-4302-a32c-e205a887db0b · outbound

This paper cites Nonblocking assignments in verilog synthesis, coding styles that kill!.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Nonblocking assignments in verilog synthesis, coding styles that kill!

Reference 18

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source=pdf_text observed=2026-08-01T19:12:13.085703Z digest=sha256:d109c7f8e9255ca040182bb18e74c305977d9ef8f2341cbfdf0266cc250d59b6

Observation 3c067d37-2c26-4771-ae75-b96d04decf6d · outbound

This paper cites Secv: Llm-based secure verilog generation with clue-guided exploration on hardware-cwe knowledge graph,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Secv: Llm-based secure verilog generation with clue-guided exploration on hardware-cwe knowledge graph,

Reference 19

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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=2026-08-01T19:12:13.196650Z digest=sha256:bc27401a547d102f51352b222b8bfbf30c6142458d352b8797e8fffda24a6e4a

Observation c228a5c7-14df-473c-91a6-ba680a4e73b8 · outbound

This paper cites Secfsm: Knowledge graph-guided llms for generating secure verilog code of finite state machine in socs,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Secfsm: Knowledge graph-guided llms for generating secure verilog code of finite state machine in socs,

Reference 20

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source=pdf_text observed=2026-08-01T19:12:13.310443Z digest=sha256:ea8bd8dfa71a06fc5c129fbe4ec9f9a5ff54194cd9b3d1fcd29660876e387ce2

Observation c960fe16-40d7-4547-8447-a1ef52a6030a · outbound

This paper cites Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification

Reference 21

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source=pdf_text observed=2026-08-01T19:12:13.427128Z digest=sha256:7d6251596e88266bacd611eca24f585c83971a34b6f38f22b92198c6338167a5

Observation aeabe0b3-2545-45e3-9a0d-0a47c4409656 · outbound

This paper cites Chatgpt outperforms crowd workers for text-annotation tasks,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Chatgpt outperforms crowd workers for text-annotation tasks,

Reference 22

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source=pdf_text observed=2026-08-01T19:12:13.574461Z digest=sha256:a7fc3588589c64fd074039de3be89ec2c1d57df1ff054aa2137505ce9bf47e81

Observation 5f501d96-fc84-48d4-a778-600673394411 · outbound

This paper cites ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning

Reference 23

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source=pdf_text observed=2026-08-01T19:12:13.721189Z digest=sha256:7fb9e8277db91c2ca92928dac28c8b1b8ef3bb4aacdf20fa57e9ae0a978b33aa

Observation 0036bd12-99df-45e9-b518-6df377d68ff3 · outbound

This paper cites an unresolved cited work.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-01T19:12:13.918544Z digest=sha256:b94a499edf3f6ce5860cba85c0315ef5325b11c4d4eb58ed2d16fc9259352a11

Observation 27a6340f-5711-4242-84c6-eaae34a27362 · outbound

This paper cites Probable inference, the law of succession, and statistical inference,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Probable inference, the law of succession, and statistical inference,

Reference 25

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source=pdf_text observed=2026-08-01T19:12:14.057808Z digest=sha256:12d94bba43601456a36415a594b827197983f042cba931ac8e93c09dfe2b7eaa

Observation a0622c7f-c310-49fe-8aaa-7847343da2b2 · outbound

This paper cites The measurement of observer agreement for categorical data,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering The measurement of observer agreement for categorical data,

Reference 26

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source=pdf_text observed=2026-08-01T19:12:14.200105Z digest=sha256:b8f70c493a07584a762bc7cc3d8e6d22745c4f52f5ee3b4bdb4bbde0879f75b7

Observation 57418aee-2d7e-4e14-bf8f-e18de30b6951 · outbound

This paper cites Improving Factuality and Reasoning in Language Models through Multiagent Debate.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Improving Factuality and Reasoning in Language Models through Multiagent Debate

Reference 27

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source=pdf_text observed=2026-08-01T19:12:14.312536Z digest=sha256:213f663b4504573bcf5ba50afdf376658770238e51b7a5c32f1e12c94341e1db

Observation 2089a97d-4a57-492b-9645-98f9eb3d2fb2 · outbound

This paper cites Benchmarking large language models for auto- mated verilog rtl code generation,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Benchmarking large language models for auto- mated verilog rtl code generation,

Reference 28

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source=pdf_text observed=2026-08-01T19:12:14.402460Z digest=sha256:e8f14f7cf9dd0b4525a3a8cb8ef54b54e551b9d9954250b0f9e4e63b319df053

Observation 9a6e05f9-a98d-4c53-93fc-e6d00fc843d2 · outbound

This paper cites Origen: Enhancing rtl code generation with code-to-code augmentation and self-reflection,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Origen: Enhancing rtl code generation with code-to-code augmentation and self-reflection,

Reference 29

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source=pdf_text observed=2026-08-01T19:12:14.483190Z digest=sha256:b31358eb2d96907fb910cfd5b50091d6e0f0506c36703209c1dd39919e907f1f

Observation 421d596e-7eaa-49b2-a4bd-56427f9a56dd · outbound

This paper cites What makes a good code example?: A study of programming q&a in stackoverflow,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering What makes a good code example?: A study of programming q&a in stackoverflow,

Reference 30

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source=pdf_text observed=2026-08-01T19:12:14.567244Z digest=sha256:ed6db8b8ece5e5eaf3102b65d2e81a9f9351efaa669384b05bb001355a192438

Observation e52ecf32-01b4-4c35-bc40-01eb55185464 · outbound

This paper cites Mining successful answers in stack overflow,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Mining successful answers in stack overflow,

Reference 31

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source=pdf_text observed=2026-08-01T19:12:14.695833Z digest=sha256:45eb606f6a16214ee72761105f616bb223d999a9b42d0658fc63dbe6cb24a916

Observation e8196ec7-3746-48f0-853f-fec0c6970298 · outbound

This paper cites Is stack overflow obsolete? an empirical study of the characteristics of chatgpt answers to stack overflow questions,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Is stack overflow obsolete? an empirical study of the characteristics of chatgpt answers to stack overflow questions,

Reference 32

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source=pdf_text observed=2026-08-01T19:12:14.751507Z digest=sha256:f39dc2b831d91629f1d2aba06ae36fd8175ebbf31b40eca520ee0aa993870a3a

Observation 1b925489-651c-4d26-9571-1f68510c24cb · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Metagpt: Meta programming for a multi-agent collaborative framework,

Reference 33

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:14.822304Z digest=sha256:3d4d851b7e4ee638c05db3b5a5d18d83c8aa85d019e1f64250b8e03df8764ea3

Observation 27e5ba96-5c52-4996-ac5f-ae0f60e2ce7e · outbound

This paper cites Agentverse: Facilitating multi- agent collaboration and exploring emergent behaviors,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Agentverse: Facilitating multi- agent collaboration and exploring emergent behaviors,

Reference 34

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source=pdf_text observed=2026-08-01T19:12:14.992161Z digest=sha256:70915e6f66e1f30d9378d507530ddef8945f4a2815747d444ac2d34ca1054b57

Observation 13224202-451c-4898-9f43-eed3e50cc2d1 · outbound

This paper cites Chateval: Towards better llm-based evaluators through multi- agent debate,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Chateval: Towards better llm-based evaluators through multi- agent debate,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-01T19:12:15.067166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:15.067166Z digest=sha256:94116189741716319ca9073bcf7b173574a4e64114375bc1f1465b96aecac674

Observation 2de66c34-7727-45b5-be01-5b662d148fb9 · outbound

This paper cites VeriMind: Agentic LLM for Automated Verilog Generation with a Novel Evaluation Metric.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering VeriMind: Agentic LLM for Automated Verilog Generation with a Novel Evaluation Metric

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-01T19:12:15.233767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:15.233767Z digest=sha256:174071d7e70dd1b7f9c77d996bd85b83fe922f299c51c2c3e178ef3f2dcc55ea

Observation aa029a67-6fab-4c9d-94d3-be9636a9d914 · outbound

This paper cites RTLSquad: Multi-Agent Based Interpretable RTL Design.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering RTLSquad: Multi-Agent Based Interpretable RTL Design

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-01T19:12:15.394005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:15.394005Z digest=sha256:2aaabe038d3d3ee81580ab281848986b2b5c83dcaec579607e9f25919aa5f7bb

Observation 290d9e8a-8fc3-4a14-b1ae-a8191424945d · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering Judging llm-as-a-judge with mt-bench and chatbot arena,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-01T19:12:15.532002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:15.532002Z digest=sha256:5aa660f1697417948ea00659d9ebc81ff5dc206e0b1d034a601a05c364d6cff8

Observation 013340b0-47ed-41bf-abb9-849605395517 · outbound

This paper cites G-eval: Nlg evaluation using gpt-4 with better human alignment,.

When LLMs Over-Answer: Measuring and Mitigating Quality Issues in LLM-Based Hardware Description Language Question Answering G-eval: Nlg evaluation using gpt-4 with better human alignment,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-01T19:12:15.717303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T19:12:15.717303Z digest=sha256:716068d8ab3bd9a9b5409b34ef3892c5e0f66300b995f70e9f66d69a8366e3e3

Pith citing papers

No inbound Pith citation observations are available.