Pith. sign in

Paper Citation Record · LEDGER

Can language models learn from explanations in context?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2204.02329.

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

pith.paper-citation-record.v1
2204.02329 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:54:26.283373Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T12:05:43.556051Z

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 3a8be2a6-d356-455c-a55b-e0d48e28d7ce · inbound

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models cites this paper.

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Can language models learn from explanations in context?

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T12:54:44.749334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-10T12:54:44.636760Z digest=sha256:3c31d401e67504d28556f6e5ca0d71196e85763db513cc459fabae2e97399b23

Observation a0a602eb-cf70-4cfe-bfc5-ff876b830d89 · inbound

Emergent Abilities of Large Language Models cites this paper.

Emergent Abilities of Large Language Models Can language models learn from explanations in context?

Reference 46

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T07:38:38.390857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-11T07:38:37.734402Z digest=sha256:3b55aa30e12ba91b791146021eadfe4cf01947ae117a14389fed8331c9d9a898

Observation a0c2659d-a58a-410d-924b-72da84a49ae8 · inbound

Inner Monologue: Embodied Reasoning through Planning with Language Models cites this paper.

Inner Monologue: Embodied Reasoning through Planning with Language Models Can language models learn from explanations in context?

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:10:44.112248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T20:10:43.912935Z digest=sha256:3b23c7aa8206ad016653462c4d6e5c58ad0e7d781a4c38bc48c86a6d8a10249d

Observation 305a21fa-7344-4800-9742-eb55c66f988b · inbound

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them cites this paper.

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them Can language models learn from explanations in context?

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:15:24.053343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-11T07:15:23.725397Z digest=sha256:a73c68066990cbd562de4b63ae0d235711d02932c585e0af3847a36e338079b6

Observation 77ff3cdb-048e-4113-8a71-e92bdc94951a · inbound

Towards Expert-Level Medical Question Answering with Large Language Models cites this paper.

Towards Expert-Level Medical Question Answering with Large Language Models Can language models learn from explanations in context?

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:32:33.454104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-24T04:32:33.271634Z digest=sha256:37199ca6d34d5662e4c52b20da4c73785e1513e3f7556ab2d6f01c6e774c353a

Observation 9c64f933-4f80-42e5-80d6-72338f5be7a2 · inbound

PaLM 2 Technical Report cites this paper.

PaLM 2 Technical Report Can language models learn from explanations in context?

Reference 198

Resolution
verified exact
arxiv_id, observed 2026-05-12T11:59:27.264917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T11:59:25.813128Z digest=sha256:7fad8f7a49639da19aa7d2fd20043dcf4e03fff1de13be015c5329652f686e4c

Observation c781a805-b3f2-4d35-b952-eee1dbee3fc3 · inbound

Can AI Examine Novelty of Patents?: Novelty Evaluation Based on the Correspondence between Patent Claim and Prior Art cites this paper.

Can AI Examine Novelty of Patents?: Novelty Evaluation Based on the Correspondence between Patent Claim and Prior Art Can language models learn from explanations in context?

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T15:54:26.283373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T15:54:26.283373Z digest=sha256:cd9eafbf09469c36130ea69bf9de11cffab589f7dbc1ab3e9a1109b405814930

Observation b85dcbc6-d0ae-4bff-8707-431f79d4bb21 · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist Can language models learn from explanations in context?

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:02:44.779168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:08124c57b6d9f1a26dc6e9b5bcfe2d5b3cd446224a624a82c4f9e4e681718fc4

Observation 5eeef6d7-36c3-4128-bde5-dbc774d5ec4f · inbound

ReGUIDE: Data Efficient GUI Grounding via Spatial Reasoning and Search cites this paper.

ReGUIDE: Data Efficient GUI Grounding via Spatial Reasoning and Search Can language models learn from explanations in context?

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T15:25:31.511571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:25:31.511571Z digest=sha256:98de194dde6d43c7ddc47e1ddedee0076b2b37749e71ea75fa4dad439f2f4d70

Observation a95e3cf1-0923-4185-8b9e-763c1ed71513 · inbound

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis cites this paper.

Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis Can language models learn from explanations in context?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T10:42:54.763756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:42:54.763756Z digest=sha256:9a8f819987eaabaa4ed0f1719222dea6a0a08776a9af045ca4593807594c95be

Observation ab19a38f-209e-4b41-9167-133c678acb87 · inbound

Towards Transparent AI: A Survey on Explainable Large Language Models cites this paper.

Towards Transparent AI: A Survey on Explainable Large Language Models Can language models learn from explanations in context?

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T22:22:40.563473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:22:40.563473Z digest=sha256:f489502637d5f2d65954b4d2f7755946accd768d0c8eb5ba9b9f92c33bc0c833

Observation dbf52777-c65a-44b4-b99f-52f51664855c · inbound

VerifyLLM: LLM-Based Pre-Execution Task Plan Verification for Robots cites this paper.

VerifyLLM: LLM-Based Pre-Execution Task Plan Verification for Robots Can language models learn from explanations in context?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T19:37:19.927719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:37:19.927719Z digest=sha256:e3eb696c4b9ba3cbeca2bbdc42f751c3fad47c60ed667ec7fa1c2e00b490858c

Observation e4d6bfd3-38c5-4909-a15a-919032792b0b · inbound

TT-XAI: Trustworthy Clinical Text Explanations via Keyword Distillation and LLM Reasoning cites this paper.

TT-XAI: Trustworthy Clinical Text Explanations via Keyword Distillation and LLM Reasoning Can language models learn from explanations in context?

Reference 4205

Resolution
unresolved
no resolver link, observed 2026-08-06T11:22:09.529185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:22:09.529185Z digest=sha256:e79696f0c01fa7b57166f048caed82f76f9fa19056c93c2ebf5ee9d10202324b

Observation dded7cad-74d6-415a-b387-cb1b821b3597 · inbound

Understanding and evaluating computer vision models through the lens of counterfactuals cites this paper.

Understanding and evaluating computer vision models through the lens of counterfactuals Can language models learn from explanations in context?

Reference 150

Resolution
unresolved
no resolver link, observed 2026-08-05T14:49:31.208595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:49:31.208595Z digest=sha256:434c7722c82d5d22f775549604b5fd053aca7599bec291a1094bf4c241514fa7

Observation f13dcf39-3ea7-457c-b4c7-0717329cae1d · inbound

A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization cites this paper.

A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization Can language models learn from explanations in context?

Reference 28

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T12:05:43.557533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T02:32:19.425550Z digest=sha256:1b9667e8c5737ca3239f5e2506c1822b5d312c6a90b063e0d689e13d6bfb7a43

Observation df06a5ab-28c0-4566-8523-0ea5e9c18f26 · inbound

Data-Efficient Adaptation of LLMs via Attention Head Reweighting cites this paper.

Data-Efficient Adaptation of LLMs via Attention Head Reweighting Can language models learn from explanations in context?

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-02T05:16:35.721598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:16:35.721598Z digest=sha256:41b65a6457e637cebb213c839dcd2e2609cc7a96ed940afdfa20eeae4ee79d62

Observation d8b820fc-2588-4ebd-8eb6-06f69ecc221c · inbound

Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives cites this paper.

Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives Can language models learn from explanations in context?

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-01T15:26:54.994950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T15:26:54.994950Z digest=sha256:6b4b78354fc20b28ea76f20d1a9b6c1382a81a86c86eeb94a487c7dfc8c082b8

Observation 5acb0331-34cc-4d30-ac55-8b4c793315eb · inbound

Test-Time Scaling via Error Localization cites this paper.

Test-Time Scaling via Error Localization Can language models learn from explanations in context?

Reference 153

Resolution
unresolved
no resolver link, observed 2026-08-01T07:28:33.955551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:28:33.955551Z digest=sha256:6f182bdb7473f7de9e7b6539923104df17a7a7480d667ba3b540f08c2de5f641