Paper Citation Record · LEDGER

Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2402.01722.

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

pith.paper-citation-record.v1
2402.01722 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:10:53.939824Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:09:28.884922Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 81a7edd7-b860-4eee-88c8-86b7d3b240c1 · inbound

Doing More with Less: A Survey on Routing Strategies for Resource Optimisation in Large Language Model-Based Systems cites this paper.

Doing More with Less: A Survey on Routing Strategies for Resource Optimisation in Large Language Model-Based Systems Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 108

Resolution: unresolved; no resolver link, observed 2026-08-09T19:10:53.939824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b57b6951-8d90-4f3c-94ea-ec5fb8b2e330 · inbound

From Divergence to Consensus: Evaluating the Role of Large Language Models in Facilitating Agreement through Adaptive Strategies cites this paper.

From Divergence to Consensus: Evaluating the Role of Large Language Models in Facilitating Agreement through Adaptive Strategies Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T16:14:51.967500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e4cd5a1-43e0-4c78-9d6e-7bfbefa58ee6 · inbound

KaFT: Knowledge-aware Fine-tuning for Boosting LLMs' Domain-specific Question-Answering Performance cites this paper.

KaFT: Knowledge-aware Fine-tuning for Boosting LLMs' Domain-specific Question-Answering Performance Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T15:22:48.233252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc6e08ff-a687-433f-ba27-895d8c430f65 · inbound

Deep Research Agents: A Systematic Examination And Roadmap cites this paper.

Deep Research Agents: A Systematic Examination And Roadmap Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 133

Resolution: unresolved; no resolver link, observed 2026-08-06T23:26:57.012419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48e57b3c-118a-489a-9c57-1cdfb721107a · inbound

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment cites this paper.

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-05T10:34:46.856881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3840225a-e185-447c-8e7e-3466c0a981a4 · inbound

BioHarness: Substrate-Aware Evidence Assembly for Biomedical Question Answering across Literature, Knowledge Bases, and Biological Atlases cites this paper.

BioHarness: Substrate-Aware Evidence Assembly for Biomedical Question Answering across Literature, Knowledge Bases, and Biological Atlases Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:09:28.887205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 00996242-e823-477e-870d-1e93aee5a5b1 · inbound

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices cites this paper.

Less is More: Lightweight Prompt Compression for Question Answering Applications on Edge Devices Enhancing Large Language Model Performance To Answer Questions and Extract Information More Accurately

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T08:55:34.890257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.