Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Calibrate Before Use: Improving Few-Shot Performance of Language Models
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2102.09690.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-31T12:20:06.584062Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z
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 43c2c1c1-123e-40e2-81a8-a558ebf1caf8 · inbound
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models cites this paper.
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 85
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T12:54:44.815033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9575c1b5-daab-40de-863c-fa385ffb3314 · inbound
Emergent Abilities of Large Language Models cites this paper.
Emergent Abilities of Large Language Models Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 101
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T07:38:38.283201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 44ec5d43-9a94-4655-9930-48e61a3a461d · inbound
Discovering Latent Knowledge in Language Models Without Supervision cites this paper.
Discovering Latent Knowledge in Language Models Without Supervision Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T20:34:08.272099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f115fa0c-df30-4ac7-a3c3-83b8846c5a1e · inbound
Simple synthetic data reduces sycophancy in large language models cites this paper.
Simple synthetic data reduces sycophancy in large language models Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 55
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T14:48:08.751738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f3caae90-762f-40e2-a475-caa43ca87d81 · inbound
Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks cites this paper.
Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T11:10:02.029576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6719b4f3-b09e-4215-ad88-0d2cf0016e0e · inbound
Consistency Analysis of Sentiment Predictions using Syntactic & Semantic Context Assessment Summarization (SSAS) cites this paper.
Consistency Analysis of Sentiment Predictions using Syntactic & Semantic Context Assessment Summarization (SSAS) Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T11:00:03.692322Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cbe87f13-4d7c-4db7-8727-a861c6df8d48 · inbound
When Context Sticks: Studying Interference in In-Context Learning cites this paper.
When Context Sticks: Studying Interference in In-Context Learning Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T20:36:09.464038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 08df5648-85f0-49bd-ba16-739ea8688977 · inbound
Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study cites this paper.
Leveraging LLMs for Multi-File DSL Code Generation: An Industrial Case Study Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 50
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T22:26:13.413182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3518060e-cf38-468b-af03-e914ad9f9640 · inbound
AMEL: Accumulated Message Effects on LLM Judgments cites this paper.
AMEL: Accumulated Message Effects on LLM Judgments Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:11:06.762175Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7e90e6ff-17fc-448e-90be-f5211dfe758b · inbound
AMEL: Accumulated Message Effects on LLM Judgments cites this paper.
AMEL: Accumulated Message Effects on LLM Judgments Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T17:04:56.429057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0394aa37-285e-468d-8f6e-d7c57a26396a · inbound
The Tokenizer Tax Across 25 European Languages: Domain Invariance, Cross-Lingual Few-Shot Effects, and the Ukrainian Penalty cites this paper.
The Tokenizer Tax Across 25 European Languages: Domain Invariance, Cross-Lingual Few-Shot Effects, and the Ukrainian Penalty Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T13:14:40.898485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3ffd7d1b-0f14-4730-bfe1-8b04604c36e4 · inbound
UA-Legal-Bench: A Benchmark for Evaluating Large Language Models on Ukrainian Legal Reasoning cites this paper.
UA-Legal-Bench: A Benchmark for Evaluating Large Language Models on Ukrainian Legal Reasoning Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 15
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T12:23:24.536134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d93c0237-f6f9-4dba-9e95-256509827e67 · inbound
Supervision versus Demonstration-Based In-Context Learning for Multiword Expression Classification cites this paper.
Supervision versus Demonstration-Based In-Context Learning for Multiword Expression Classification Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 219
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T17:27:14.909483Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2cdc9b74-bbd5-45d9-9142-1971a6c52cc0 · inbound
PRIME: Evaluating Prompt Resolution Under Incompatible Instructions in LLMs cites this paper.
PRIME: Evaluating Prompt Resolution Under Incompatible Instructions in LLMs Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T08:49:41.704426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b49f1bd0-4cc1-4abf-a062-4043cebe7476 · inbound
(Towards) Scalable Reliable Automated Evaluation with Large Language Models cites this paper.
(Towards) Scalable Reliable Automated Evaluation with Large Language Models Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T12:20:06.584062Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.