Paper Citation Record · LEDGER

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation

As of 9 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 1 inbound Pith citation observation for arXiv:2602.09130.

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

pith.paper-citation-record.v1
2602.09130 v5

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T03:07:44.420625Z

measured 10 of 10 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T10:01:02.442335Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

9 of 9 outbound references displayed

verified exact0
verified fuzzy0
unresolved8
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation d81cdbeb-e737-4f79-8741-3fdbbcfd6954 · outbound

This paper cites TruthfulQA: Measuring How Models Mimic Human Falsehoods.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation TruthfulQA: Measuring How Models Mimic Human Falsehoods

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.403315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 906feaee-1255-47a8-909b-097d40f3347d · outbound

This paper cites Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.414501Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14cb807a-f830-4c08-8cef-048a36f4297d · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.417751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95c35b37-d543-44c7-9fec-3365fc6486e7 · outbound

This paper cites InProceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11794–11812, Torino, Italia.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation InProceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11794–11812, Torino, Italia

Reference 9

Resolution: malformed identifier; no resolver link, observed 2026-08-03T03:07:44.420625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aebc39bd-d736-44e6-9005-fea783022173 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation Distilling the Knowledge in a Neural Network

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.400075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 887cd39b-d035-43e0-a728-e711fec8dd92 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation Training Verifiers to Solve Math Word Problems

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.396544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69876efe-cefd-4c00-9779-cb4a621eed14 · outbound

This paper cites LLM Pruning and Distillation in Practice: The Minitron Approach.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation LLM Pruning and Distillation in Practice: The Minitron Approach

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.410691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08166822-1dfd-46aa-970b-e343ab9a57fa · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.392593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2c3ea5d-9691-4407-a4fb-898ca0a234d5 · outbound

This paper cites AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios.

UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T03:07:44.406753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 23bccfb0-5aec-4960-b248-ea64fc180a28 · inbound

Quantizing Recursive Reasoning Models cites this paper.

Quantizing Recursive Reasoning Models UniComp: A Unified Evaluation of Large Language Model Compression via Pruning, Quantization and Distillation

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-02T10:01:02.442335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.