Pith. sign in

Paper Citation Record · LEDGER

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation

As of 19 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 2 inbound Pith citation observations for arXiv:2412.19819.

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

pith.paper-citation-record.v1
2412.19819 v2

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:25:11.205191Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:31:23.486344Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:31:01.045059Z

Reference resolution

32 of 32 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a2a0fd4-3950-4b6a-81c3-3f5100bdb000 · outbound

This paper cites GPT-4 Technical Report.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:10.976379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:10.976379Z digest=sha256:7e71e7e419acdac36a5dddc6b8629a2643cd3a101c41bde565193455c8737d92

Observation 9abc312d-5c1d-4069-a06d-792f4a5622cf · outbound

This paper cites Information geometry and manifolds of neural networks.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Information geometry and manifolds of neural networks

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.154270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:10.983937Z digest=sha256:136da01da0774e496f113d6f82a1123df9e2142c04bf8cd3314e308729735d33

Observation 50522ba2-9b8e-4b2f-b42e-7a7463f8990b · outbound

This paper cites Information geometry of boltzmann machines.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Information geometry of boltzmann machines

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.132093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:10.991860Z digest=sha256:4d923a500c30de09699c0d32da90e59a47408579a310ed78eb191e1121fe47f0

Observation 4e306068-be07-43f8-bf20-63f07dacad41 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation The claude 3 model family: Opus, sonnet, haiku

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.002147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.002147Z digest=sha256:611853f145fb1ab195b40db870bf9c0e6beb871039a51625f6dbb585c72daaba

Observation 55e4f139-a207-4d81-a86a-dc92e6ef1374 · outbound

This paper cites Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.009517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.009517Z digest=sha256:294eec2573b1556b910aeb130366e9d613a7f94214317dda1c8cf1303cc0f713

Observation 40ccd21a-15f7-416a-a43f-ac3b038c014e · outbound

This paper cites DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation DELLA-Merging: Reducing Interference in Model Merging through Magnitude-Based Sampling

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.016116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.016116Z digest=sha256:3a9c08d6c5030d2def30757e9ae2537b8d6f98d0b7040b030cd1b7c74a01cfa9

Observation 8909a967-efb2-4504-a40f-28bcc70c8c3d · outbound

This paper cites SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.024505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.024505Z digest=sha256:20e330a60c4ee32da5c11ba7abfef364c78c53cea17cb62d4a46e1d1a91312e1

Observation 11bfcc3f-4093-4c59-922f-f5398b7db78b · outbound

This paper cites The Llama 3 Herd of Models.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation The Llama 3 Herd of Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.033926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.033926Z digest=sha256:1d332bca05245931021c21e96a8c0a4fff3033d6e92da2d8f7621e41ae4a151d

Observation af11beec-4641-4430-8246-d58df601d8e7 · outbound

This paper cites A Closer Look at the Limitations of Instruction Tuning.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation A Closer Look at the Limitations of Instruction Tuning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.044370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.044370Z digest=sha256:81d8dcefbe4bf0c2c81f079ba138c292f92f563951960ba02146d86984b21815

Observation bdf81ac4-03dd-499e-ad23-e6e4e1aeba57 · outbound

This paper cites Editing Models with Task Arithmetic.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Editing Models with Task Arithmetic

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.052116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.052116Z digest=sha256:331ffe818365ace9ce702f5f4057dfd665cc07065a5b31870a027d1af55277b2

Observation a51d6399-3f13-4bb5-9f90-e21b0b273b5b · outbound

This paper cites Openassistant conversations-democratizing large language model alignment.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Openassistant conversations-democratizing large language model alignment

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.095383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.061064Z digest=sha256:396c8ffedcb1c6c3d63a41222bcdbab52e36735105022de24ecb1935baac0279

Observation 188abd3b-5d0f-4102-af59-ff87317b11b1 · outbound

This paper cites Baichuan-omni technical report.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Baichuan-omni technical report

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.066662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.066662Z digest=sha256:cb5b2d9817c1782de2c4dc9e8f016ae47b2977669efdeb37c88b4f31ab5da246

Observation 807b467b-2356-40f9-b633-028c68e7c8dc · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Rouge: A package for automatic evaluation of summaries

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.073176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.073176Z digest=sha256:9db776e4ee70b96e87c671cb0ea2ccb2bd1e6c96e784d058e2662290d7d09afd

Observation 34b0e947-1c03-494f-84a2-15495c6af29d · outbound

This paper cites ChipNeMo: Domain-Adapted LLMs for Chip Design.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation ChipNeMo: Domain-Adapted LLMs for Chip Design

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.078920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.078920Z digest=sha256:037017f0bf6956731d5fc8b0eaf0ad785166fe983cdabef6236bde7a24d6102d

Observation 033cbef5-6ca1-4048-a7ac-a9419a51df93 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Bleu: a method for automatic evaluation of machine translation

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.085061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.085061Z digest=sha256:0847c4dceb63386d7e9293d77076febbb8586470f81e8dc157f6f27941a2df91

Observation 80e00d9b-4f60-42e6-8f98-c68664313709 · outbound

This paper cites Customized Retrieval Augmented Generation and Benchmarking for EDA Tool Documentation QA.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Customized Retrieval Augmented Generation and Benchmarking for EDA Tool Documentation QA

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.093649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.093649Z digest=sha256:4abaf03dac522734d43664c59cc21161e8d75e32c16cd0c80b0cb81436b9d3bb

Observation 0f9fa8a4-c8ee-4bb4-aa6d-c7efc187cff2 · outbound

This paper cites Openroad-assistant: An open-source large language model for physical design tasks.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Openroad-assistant: An open-source large language model for physical design tasks

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.043381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.100116Z digest=sha256:284ad813cad7b05334b2671d3aec9b420c0ea787e100a31ed6b4820ddc45143a

Observation c9d734f1-88f6-4fa0-a314-e621fc9d7efd · outbound

This paper cites Animating rotation with quaternion curves.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Animating rotation with quaternion curves

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.024183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.107451Z digest=sha256:ea48f7a73563ebcc38914f5e495e35fb45ecb1de4e2a033526de8814b2f17d94

Observation 91f1dbd2-d5b5-41b3-9b68-8d160ba52459 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Gemini: A Family of Highly Capable Multimodal Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.115236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.115236Z digest=sha256:68340b0d31eabfe4ca139a39d9adb751b71e11ed54b26439a68e075185ca29c5

Observation 69dd56fc-8b53-4f38-b6fe-4cdd901501ba · outbound

This paper cites Chatclimate: Grounding con- versational ai in climate science.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Chatclimate: Grounding con- versational ai in climate science

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:12.004007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.121677Z digest=sha256:4bd93daa72079eafb499f6f92d02582dfeaa0a84536b22065528cab5ba297662

Observation c5a13035-9e6d-435d-9c7f-88e2b543fec7 · outbound

This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:11.982155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.128430Z digest=sha256:c6cb5259557322d4d0bfa7163198632033e25cb9a316e88882614ff69ac2b70d

Observation 9da65d1c-945a-4175-a587-2db1a3f8f35c · outbound

This paper cites Pmc-llama: toward building open-source language models for medicine.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Pmc-llama: toward building open-source language models for medicine

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.135374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.135374Z digest=sha256:08ed399377108e766849f6adfe7496f77bba734c5bdc23c79fb55bcf86e18215

Observation 3fb923aa-33ef-4b2c-bff7-63ae7a7622ba · outbound

This paper cites Chateda: A large language model powered autonomous agent for eda.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Chateda: A large language model powered autonomous agent for eda

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:11.950829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.141719Z digest=sha256:f90c05521b1541f8effdaeb80c3cf905cb19f055dfe58e8e44513e5bf5e46a58

Observation 25491cf1-171a-48a8-9fe8-17464608d3f5 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation BloombergGPT: A Large Language Model for Finance

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.150496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.150496Z digest=sha256:767f938b952828f3478e31550869e4fd95a3e8a5015ec04f5fb525a95e3ac315

Observation 7b864e78-08e8-48a1-93ac-fe76c208efd4 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation C-Pack: Packed Resources For General Chinese Embeddings

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.157220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.157220Z digest=sha256:659092ac225f755b730eedd8d42898e0ec4f65447dcebfea4206d66e349d95c5

Observation f155f4f2-7aaf-42d9-99c6-e6c29d4f6d7d · outbound

This paper cites Ties-merging: Resolving interference when merging models.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Ties-merging: Resolving interference when merging models

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T15:25:11.931576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T15:25:11.167261Z digest=sha256:6e26538a6cddc57534f36499a6639f0b5c8c7005303b8925de91d9ea97150147

Observation e9b1a593-4284-40b5-a264-67073845f1d4 · outbound

This paper cites Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.172774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.172774Z digest=sha256:c033f9ff39805ebc31e849218aad0378f01f01a782f4c1f71db9a995e04a4aae

Observation c467fa8b-c9ba-4681-911f-4738f5e40cb4 · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.179393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.179393Z digest=sha256:620804c117b5cffdc73bf30e982dfc56cb1fbbd08499e59bc3c9430e477a70d3

Observation e80d033d-17e7-48b4-8b9b-33c7ae839fe6 · outbound

This paper cites RAFT: Adapting Language Model to Domain Specific RAG.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation RAFT: Adapting Language Model to Domain Specific RAG

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.185998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.185998Z digest=sha256:795382eef275f18d39e44bdaeda686b7acbd4095df8a67817e4d0c448fd6a40f

Observation 68d6bd32-1a93-4111-96e0-93567468bf16 · outbound

This paper cites A Survey of Large Language Models.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation A Survey of Large Language Models

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.193366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.193366Z digest=sha256:cb7b22e20c216455b04f6cfb60fdc096cdd73da714c031c5d78f08371fea389a

Observation 60bc0460-54e5-4a2c-9433-fd12e7793f24 · outbound

This paper cites Towards a Unified Multi-Dimensional Evaluator for Text Generation.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Towards a Unified Multi-Dimensional Evaluator for Text Generation

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.199586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.199586Z digest=sha256:d54f0e5b5b2b544e39523f7a3f43dac1a4c53b9fbb8433c49e89c6d481170b96

Observation 358f4911-db72-4693-8933-52fbb530fbbf · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation Instruction-Following Evaluation for Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-11T15:25:11.205191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:25:11.205191Z digest=sha256:eb94257fafc30806118a7eaba71960a0155870a57a07d9f7447589813e7837ed

Pith citing papers

Observation ae5b6679-2895-49fa-a5d4-4ac82aff1747 · inbound

Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors cites this paper.

Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T21:31:23.486344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:31:23.486344Z digest=sha256:5017dc35601faf5536f6aa4468b35addb9c9be205539b44e0fb6aed54916e5f9

Observation 07f317d7-91f4-4f6c-a8d0-7476bbe860d0 · inbound

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems cites this paper.

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems ChipAlign: Instruction Alignment in Large Language Models for Chip Design via Geodesic Interpolation

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:31:01.052482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-07T00:31:00.539798Z digest=sha256:0f10b4c585de1c23ef11f5fffd41dd098d37f0d4e5410c555a16189850708575