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Paper Citation Record · LEDGER

A Survey on In-context Learning

As of 12 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 100 inbound Pith citation observations for arXiv:2301.00234.

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

pith.paper-citation-record.v1
2301.00234 v6

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T12:58:27.430374Z

measured 113 of 113 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 100 of 296 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:05:51.533529Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

13 of 13 outbound references displayed

  • verified exact4
  • verified fuzzy1
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch7

External citation measurements

252
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 4f1ba566-78e6-43fd-be1c-f3824c0edbbf · outbound

This paper cites ICL Markup: Structuring In-Context Learning using Soft-Token Tags.

A Survey on In-context Learning ICL Markup: Structuring In-Context Learning using Soft-Token Tags

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.541333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:5d15151edea293091c882c8e609f6eb19f98268654a227ec255282e3a62f7c7e

Observation 734ab5eb-5bbc-4f38-b2dd-b669c176afb9 · outbound

This paper cites Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks.

A Survey on In-context Learning Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.479858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:8e59ccf5e4c8c9214006e75dd9e892c7599e0e23054f13c757bc487c4724f173

Observation 49dd6ec9-ee59-4f29-8caa-5f85df33b0d0 · outbound

This paper cites Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression.

A Survey on In-context Learning Transformers Learn to Achieve Second-Order Convergence Rates for In-Context Linear Regression

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.487969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:aa10e44894b042e7df7de35777ca4af586d1d569a4ad46fcab8a023c034eac52

Observation 0eda0d60-6099-463b-b4d7-5310049b9cc3 · outbound

This paper cites A Theory of Emergent In-Context Learning as Implicit Structure Induction.

A Survey on In-context Learning A Theory of Emergent In-Context Learning as Implicit Structure Induction

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.496176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:f0db8dcae463b3d1d8264f1c9da33841fb9822efe034dc2ce134644f6bef252c

Observation 5ebcbc09-ab92-4f8d-87b6-63ff0647c62f · outbound

This paper cites Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models.

A Survey on In-context Learning Self-Demos: Eliciting Out-of-Demonstration Generalizability in Large Language Models

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.504434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:92ae244f22207f27ea44e9028fab6911130a2ec548a7eeaaf9a5e8deefc3e6de

Observation d3a02ee1-3937-426a-b3fa-ddb9522938c6 · outbound

This paper cites A Latent Space Theory for Emergent Abilities in Large Language Models.

A Survey on In-context Learning A Latent Space Theory for Emergent Abilities in Large Language Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.514920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:1e0ff76565cad92bbc1bdcdfda4e595b33eac9ad74258414ff141f39dd1099f7

Observation 1006200d-da09-42c1-b7c9-f1d78b52f0c9 · outbound

This paper cites One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention.

A Survey on In-context Learning One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.523967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:2c47fdcf3c102acc1e713d784294361a04080e0c09b0e0103db9b7289133a294

Observation 7a484d24-846e-4721-8cf5-f41ea9083936 · outbound

This paper cites an unresolved cited work.

A Survey on In-context Learning Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-05-12T12:58:27.563978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:c5309c862ca2c7a9bd042a203403e0d8a4a927a58f9923e1fd898308fb93a5f5

Observation a8d7fcd6-955c-4bce-8e16-aca8cdf94b8b · outbound

This paper cites Do pretrained Transformers Learn In-Context by Gradient Descent?.

A Survey on In-context Learning Do pretrained Transformers Learn In-Context by Gradient Descent?

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.549625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:1e4c470f8ce93dad345b6759e0d1df8d55cb5129f580f6b12a86f7b0337bf881

Observation 4648f200-ceaf-41e9-9635-e36dee31d635 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

A Survey on In-context Learning Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-12T12:58:27.557343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:61538549ff7d0af2393227ec6f71a2e4717074bb7752ab406c372f7c4c056009

Observation 62377aec-c689-4e69-9860-f75936b24e17 · outbound

This paper cites Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models.

A Survey on In-context Learning Pretraining Data Mixtures Enable Narrow Model Selection Capabilities in Transformer Models

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.531557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:5d801826db789d5e3eb5093be642d6d33e6377029c089059789013d08079bf7a

Observation 8f8ccd7e-a54a-4a20-8868-0d8be48822e8 · outbound

This paper cites Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C.

A Survey on In-context Learning Hattie Zhou, Azade Nova, Hugo Larochelle, Aaron C

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T12:58:27.571423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:27a6c020a6db5b9a1989f3e860038adb7312e1020c69bf39a0ee57ae8f957e71

Observation f98d3c50-1454-4644-9c34-7bc811d28e56 · outbound

This paper cites Teaching Algorithmic Reasoning via In-context Learning.

A Survey on In-context Learning Teaching Algorithmic Reasoning via In-context Learning

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.469828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T12:58:27.430374Z digest=sha256:9230530538d85175fde19f90fb39ec1508dfb1412f14abc80a189627d40ea957

Pith citing papers

Observation ee11d0ec-ce07-4be8-851b-267d4b4941c5 · inbound

A Survey of Large Language Models cites this paper.

A Survey of Large Language Models A Survey on In-context Learning

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.573752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T22:46:39.268353Z digest=sha256:6c20d3fe4c1195b76f3e3f97aa2e13031aca3592fa2582350e5effe7ac14d76b

Observation 92824c87-9ddb-4b33-af1a-f233e23c4cfe · inbound

Large Language Models are not Fair Evaluators cites this paper.

Large Language Models are not Fair Evaluators A Survey on In-context Learning

Reference 55

Resolution
metadata mismatch
local_arxiv, observed 2026-05-17T12:10:42.369513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-17T12:10:42.248005Z digest=sha256:9b6d3fd36141efe8cba48d65802c0e2ae218bcaf8779f093ea78c013f21d5019

Observation 196cda7d-0fa0-48e0-9559-ceae31713870 · inbound

PaLI-X: On Scaling up a Multilingual Vision and Language Model cites this paper.

PaLI-X: On Scaling up a Multilingual Vision and Language Model A Survey on In-context Learning

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-05-17T14:36:10.041563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-17T14:36:09.971825Z digest=sha256:e717d6a8e6ef3174505d8a3e3d0e93218e1ba53c53aa5d10904ba5df722bb7c8

Observation 47cb8d86-928c-4843-a2dc-61c6a78bb39a · inbound

A Survey on Multimodal Large Language Models cites this paper.

A Survey on Multimodal Large Language Models A Survey on In-context Learning

Reference 170

Resolution
verified exact
local_arxiv, observed 2026-05-16T02:56:42.069147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-16T02:56:41.658658Z digest=sha256:e25a1757cae2718b4df5dfdc2eef69f4e85e60ca2b62efd0884ec4ecb2374e6a

Observation 12dc03ef-a0ba-46b5-a134-92dedc986ed2 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models A Survey on In-context Learning

Reference 54

Resolution
verified exact
local_arxiv, observed 2026-05-19T20:28:39.488216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T20:28:38.900026Z digest=sha256:a8ce91cd4f746761d868a8cc8f2ec435713a1627e5be845919a4bd00aea6aa6a

Observation a4ed8547-7362-4fae-851c-870c6563db5c · inbound

The Rise and Potential of Large Language Model Based Agents: A Survey cites this paper.

The Rise and Potential of Large Language Model Based Agents: A Survey A Survey on In-context Learning

Reference 196

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.573752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-11T10:47:44.152066Z digest=sha256:590336522529c5956dcf3b856afa70b3b77d53d80d33e4e9674fc1eb8a736a22

Observation 7d9526f6-dc8e-47a8-9127-551d67be58b7 · inbound

The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) cites this paper.

The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) A Survey on In-context Learning

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-05-15T23:26:06.480273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T23:26:06.183574Z digest=sha256:5c64c277c906789dd2921207fc7364e6ea7f1beddf5a93d526f032b0a6c0713a

Observation 57127118-7496-40ff-aa94-e4c757d30b27 · inbound

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V cites this paper.

Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V A Survey on In-context Learning

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-12T14:01:50.013589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T14:01:49.854238Z digest=sha256:c7aad7ab8136709a718e8c5f508ad71a567233de342156cf0b0b5a47fa4f0c35

Observation d7c2400f-25cd-4bc5-bf04-5294cde74196 · inbound

Data-Centric Foundation Models in Computational Healthcare: A Survey cites this paper.

Data-Centric Foundation Models in Computational Healthcare: A Survey A Survey on In-context Learning

Reference 76

Resolution
verified exact
local_arxiv, observed 2026-05-24T04:13:53.112503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T04:13:05.328492Z digest=sha256:0fd0686d8d2623244fbde6e126d2f7e7e347c744d57bd5fc0b2192ce3402330e

Observation d5edaffa-c1f7-4d05-8775-6ff03c6944a9 · inbound

Agent AI: Surveying the Horizons of Multimodal Interaction cites this paper.

Agent AI: Surveying the Horizons of Multimodal Interaction A Survey on In-context Learning

Reference 70

Resolution
metadata mismatch
local_arxiv, observed 2026-05-18T14:25:59.281424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-18T14:25:58.876978Z digest=sha256:d8164e3ad2e75411c2d8c948d57e4aed0f193f5b21c790473ab944e197e45146

Observation 638afc8d-d3a5-4c72-a56d-f291e10cb0c7 · inbound

Large Language Models: A Survey cites this paper.

Large Language Models: A Survey A Survey on In-context Learning

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-12T12:58:27.573752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-11T15:22:54.023279Z digest=sha256:e4cec40d9da555a2a394498527e8881d531aed363dd038843f4f38765b0a277c

Observation d554ff89-d483-4423-ae53-7227a93f3e20 · inbound

CodeMind: Evaluating Large Language Models for Code Reasoning cites this paper.

CodeMind: Evaluating Large Language Models for Code Reasoning A Survey on In-context Learning

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-05-24T03:55:59.583157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T03:53:55.964755Z digest=sha256:7bab748f037afa71ef68a3673d38fe0e62f2bec7b08a9b4835f1be0368d486cf

Observation eb039e4a-6101-4844-9e81-6a53d800f35f · inbound

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code cites this paper.

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code A Survey on In-context Learning

Reference 200

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T12:58:27.573752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-10T17:34:42.565806Z digest=sha256:3d5ce06acda51be2dab5f4245e07f99d8424951faf7e5c0f52f577a18c6bcb5a

Observation 8a24619d-9ab5-43bf-ac56-72eadf12bc79 · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models A Survey on In-context Learning

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-05-15T02:39:33.310788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T02:39:33.007894Z digest=sha256:c0604523cd10db1e64a45e4387ce293b9c19b807d4cabe14ff148019565b2598

Observation b0217751-4e1d-4da4-9307-74b3e7105e24 · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation A Survey on In-context Learning

Reference 70

Resolution
verified exact
local_arxiv, observed 2026-05-13T20:18:06.736678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T20:18:06.304134Z digest=sha256:9e07ba9d7600e5e2901c4aa4492262b45d7623fd52382e314b7fc9249aa298c6

Observation 47f44f1a-2de6-4534-a8c4-75feddd29b98 · inbound

Benchmark Data Contamination of Large Language Models: A Survey cites this paper.

Benchmark Data Contamination of Large Language Models: A Survey A Survey on In-context Learning

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-22T23:10:40.911606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-22T23:10:40.420241Z digest=sha256:436c6776e80347f0100d7bdd526e31db55f4d4f0b0fea7fb360f615a300c43e0

Observation 0f97e1e2-508c-4f0c-90f1-67d95a7f5c82 · inbound

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning cites this paper.

E2LLM: Encoder Elongated Large Language Models for Long-Context Understanding and Reasoning A Survey on In-context Learning

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-23T20:38:25.062998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-23T20:36:55.159302Z digest=sha256:a21f8c4dc3fa9ce12bb6ec1ff1d709b8c77a12d0e3495ebe9ca373d9502320e6

Observation 3b71048a-ebb4-4e98-a5cc-709579ec527e · inbound

Recent Advances in Multimodal Affective Computing: An NLP Perspective cites this paper.

Recent Advances in Multimodal Affective Computing: An NLP Perspective A Survey on In-context Learning

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-23T21:23:27.766552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T21:19:06.228443Z digest=sha256:78be208e87d55d06ccdf77e5fab05b72b86e0a939d8652e62475d4d2a02a7cdc

Observation 34d24ba6-fc98-4fad-998d-a76db9da36f6 · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey A Survey on In-context Learning

Reference 98

Resolution
verified exact
local_arxiv, observed 2026-05-19T11:08:27.652010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T11:08:27.472508Z digest=sha256:083a4cc07399742980c09eb4533b67c28c43cf11d4eae1c76b61df065e037691

Observation ce5e950a-93cc-4fb1-aedc-f8bb2ac27526 · inbound

Embodied Red Teaming for Auditing Robotic Foundation Models cites this paper.

Embodied Red Teaming for Auditing Robotic Foundation Models A Survey on In-context Learning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T11:05:51.533529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:05:51.533529Z digest=sha256:f8067ff2e7917ddee3b5b4af720905ed0fbf0db673e19953e677bc3cf52ac7b0

Observation d2ae367e-987f-414c-a4b3-38f79d8bc01c · inbound

ICLERB: In-Context Learning Embedding and Reranker Benchmark cites this paper.

ICLERB: In-Context Learning Embedding and Reranker Benchmark A Survey on In-context Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T10:46:45.978460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:46:45.978460Z digest=sha256:25627537b59ab8327ee27ac0e8975f8e2ea0508212f60729f1efa34200a39acf

Observation f9f6bda5-f864-453f-91e0-f312735bac12 · inbound

Action Engine: Automatic Workflow Generation in FaaS cites this paper.

Action Engine: Automatic Workflow Generation in FaaS A Survey on In-context Learning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-12T10:10:21.942679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:10:21.942679Z digest=sha256:dff2398805c7c56128c0d6b5a13a3f5bd72dcf7ab93317a609c96eac4767aa7b

Observation 98e61bb7-6ee9-4382-b962-b1e920047e59 · inbound

Differential learning kinetics govern the transition from memorization to generalization during in-context learning cites this paper.

Differential learning kinetics govern the transition from memorization to generalization during in-context learning A Survey on In-context Learning

Reference 6

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source=pdf_text observed=2026-08-12T10:58:18.271240Z digest=sha256:827b0667cef04c990b4581b34e335a4027509c4f21da0148d02ffe8002f9a4ce

Observation 13268050-141c-45dc-9aa4-7f416ee5a2bf · inbound

Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs cites this paper.

Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs A Survey on In-context Learning

Reference 24

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source=pdf_text observed=2026-08-12T05:24:34.060698Z digest=sha256:0269c5037498538183c2e5ba587c74fef5768ecb7a67b068fcf7a6f7d8dcd451

Observation 1f98b5c9-f068-4730-8ff2-c05f0c2dda94 · inbound

PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation cites this paper.

PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generation A Survey on In-context Learning

Reference 5

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source=pdf_text observed=2026-08-12T05:16:59.408617Z digest=sha256:f962a6c0b2b373783d253f89e4a143e4e16a8a19191093be9358a1d9bd30134c

Observation c98577e1-420e-4493-ac49-9140e22d512e · inbound

Towards Adaptive Mechanism Activation in Language Agent cites this paper.

Towards Adaptive Mechanism Activation in Language Agent A Survey on In-context Learning

Reference 12

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source=arxiv_source observed=2026-08-12T05:09:47.738697Z digest=sha256:54f92f1f5337fd14fa2da43fd1f97207b40c27787da342f980345f6215029e71

Observation 55d85c64-64ef-4bd7-bef9-1f6995a75538 · inbound

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs cites this paper.

Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAs A Survey on In-context Learning

Reference 9

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source=pdf_text observed=2026-08-11T23:49:02.178226Z digest=sha256:ec99ca4d259820461499700627eb9b1f41e662b5ce2fda9ca3a00109700beb64

Observation 7bcad955-40a4-40e1-a3e2-0cca58d5cbc4 · inbound

A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis cites this paper.

A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis A Survey on In-context Learning

Reference 5

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source=arxiv_source observed=2026-08-11T23:42:09.624150Z digest=sha256:51d07d2b7815fa7bda23bf873b4a7c4e459cb1b5f0869913200d29aa224dfc14

Observation 4b593247-63a0-4b75-86c1-ef8659396043 · inbound

Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining cites this paper.

Gracefully Filtering Backdoor Samples for Generative Large Language Models without Retraining A Survey on In-context Learning

Reference 11

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source=arxiv_source observed=2026-08-11T23:32:37.265187Z digest=sha256:ac9f2d5891e778b55c20695e2f67ac456351e0a73436186e61aa66669944f723

Observation 5fe91024-755d-415d-a84c-e1d43de7d305 · inbound

The broader spectrum of in-context learning cites this paper.

The broader spectrum of in-context learning A Survey on In-context Learning

Reference 22

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source=arxiv_source observed=2026-08-11T22:10:22.670375Z digest=sha256:63757ab9745c7ab084e84572ee447f5ba6979fd2789ce184c2424e775d4891ee

Observation faded445-9e9b-4090-876b-fa96ff7f1cad · inbound

Towards Data Governance of Frontier AI Models cites this paper.

Towards Data Governance of Frontier AI Models A Survey on In-context Learning

Reference 30

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source=pdf_text observed=2026-08-11T22:06:54.054633Z digest=sha256:68f30c47d44a8bed4a6c0e27af774466adf688625cb9f47a342c697c090df2d8

Observation 44db09c6-5910-4dbe-bee6-4ed39f33c9d3 · inbound

Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization cites this paper.

Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization A Survey on In-context Learning

Reference 20

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source=pdf_text observed=2026-08-11T21:10:16.309100Z digest=sha256:8ed74a3bcebc77c8aea0ba50a7b0e6da1be06ef536f489b2c79a9427bc32e38e

Observation 342adc83-70f3-4b9c-ab9f-df043912737c · inbound

CigTime: Corrective Instruction Generation Through Inverse Motion Editing cites this paper.

CigTime: Corrective Instruction Generation Through Inverse Motion Editing A Survey on In-context Learning

Reference 9

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source=pdf_text observed=2026-08-11T20:47:38.315083Z digest=sha256:d85687a7a5b0172519ac95c7d7b7e4dcc7eef29246867be44a16c30f5b9a8b72

Observation 1de6c476-b48c-4078-bb14-0937858c57d3 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods A Survey on In-context Learning

Reference 53

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arxiv_id, observed 2026-05-12T12:58:27.573752Z

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source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:36a7d3fe6eb420bfbb1f5d92960d1b7e2dba973cf68b3b3aa5f6d213e4acec62

Observation 570ae0a7-16f7-49e8-a123-ccc5b30618cc · inbound

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation cites this paper.

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation A Survey on In-context Learning

Reference 12

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source=pdf_text observed=2026-08-11T20:25:14.490817Z digest=sha256:7aa4cd421fd90d328b083641144ad1017169833bc0b5e65413cbe27bab6f86cd

Observation 36a5099a-1845-45b0-b7ac-a82cf49d6cea · inbound

Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective cites this paper.

Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective A Survey on In-context Learning

Reference 4

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source=pdf_text observed=2026-08-11T20:10:53.633581Z digest=sha256:e3dc3ac8f68fc51c331ad54093d1cd0d3eb1f1844b762c234bad9e4cf8902cf5

Observation 782d5b61-e2ad-45f6-b642-6f99d7a313b0 · inbound

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation cites this paper.

Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation A Survey on In-context Learning

Reference 4

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source=arxiv_source observed=2026-08-11T19:03:01.093000Z digest=sha256:c4ab61d32518c0fa4cee6e00feb8ffbede834c81d254db44987a00390fb4179f

Observation c8b01ed7-0bdc-4f22-b963-d100ca26e376 · inbound

Using Large Language Models for Parametric Shape Optimization cites this paper.

Using Large Language Models for Parametric Shape Optimization A Survey on In-context Learning

Reference 56

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source=pdf_text observed=2026-08-11T18:19:53.946162Z digest=sha256:5a648454472195e44f7677aa0fd50b706d1f9ed0dcdb7ca95ca6170c74838e5d

Observation a4e426b1-194b-4ec6-bf49-3b75a6058abb · inbound

Magneto: Combining Small and Large Language Models for Schema Matching cites this paper.

Magneto: Combining Small and Large Language Models for Schema Matching A Survey on In-context Learning

Reference 24

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source=pdf_text observed=2026-08-11T18:10:19.709087Z digest=sha256:1c8ab132758451b00189c841f7810d4e89aa0464aecf3fd1f7029656c02781fd

Observation 76716d8a-b0b7-4683-b004-930eec04fc31 · inbound

TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch cites this paper.

TouchTTS: An Embarrassingly Simple TTS Framework that Everyone Can Touch A Survey on In-context Learning

Reference 6

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source=pdf_text observed=2026-08-11T18:08:21.360766Z digest=sha256:372c98da4bb784b8e02f0497dcdc5b52d9aadb88aee215755c713abf47e41c9f

Observation 75cfa14a-b8f9-4487-896f-7ae1df5c893d · inbound

RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios cites this paper.

RuleArena: A Benchmark for Rule-Guided Reasoning with LLMs in Real-World Scenarios A Survey on In-context Learning

Reference 9

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source=arxiv_source observed=2026-08-11T17:25:31.514193Z digest=sha256:94070d771cb062a3483b69356f276fca28378257abd67d654120f887f890e530

Observation 09533c2e-5ceb-45b0-8a18-76a3f62062c0 · inbound

Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator cites this paper.

Learning to Solve Domain-Specific Calculation Problems with Knowledge-Intensive Programs Generator A Survey on In-context Learning

Reference 7

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source=arxiv_source observed=2026-08-11T17:11:09.130903Z digest=sha256:0e305eabd2185360f03022d33e192559a24b2bfb32000c403e0f666c78d4621f

Observation 5df1a884-bac9-4943-b96b-a3356a1aafdd · inbound

Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning cites this paper.

Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning A Survey on In-context Learning

Reference 7

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source=arxiv_source observed=2026-08-11T16:39:23.806153Z digest=sha256:30e32304a24c6317499fe23dc8707ca2388fbab465efa0505b999fd6b1022f00

Observation 32919527-7075-4be1-9c99-c901ae2d604c · inbound

Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data cites this paper.

Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by Quantifying Label Shifts in Synthetic Training Data A Survey on In-context Learning

Reference 12

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source=arxiv_source observed=2026-08-11T16:25:16.798670Z digest=sha256:4187fa6a10cd4c25008cf3e6e433856b6eed8704fac0807f5b184f3b0e2db6ed

Observation bf002f81-5853-4e0a-a5c4-622c955c1daf · inbound

Video Diffusion Transformers are In-Context Learners cites this paper.

Video Diffusion Transformers are In-Context Learners A Survey on In-context Learning

Reference 10

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source=pdf_text observed=2026-08-11T15:40:19.684635Z digest=sha256:54e8825c6728ac0766391751a897b5829dbb69ce5af0c182c05dd73080f671ab

Observation 8e1d516c-0a23-4d8a-a98a-21bc69f67b5d · inbound

Zero-Shot Prompting Approaches for LLM-based Graphical User Interface Generation cites this paper.

Zero-Shot Prompting Approaches for LLM-based Graphical User Interface Generation A Survey on In-context Learning

Reference 12

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source=pdf_text observed=2026-08-11T15:07:30.314477Z digest=sha256:5b2b66b1e0dd616b0f8672982879d17152906e8ae164643a808f2e58e53d5ba2

Observation e5f720c5-adb8-4fbf-8014-e06bc0cbcde0 · inbound

Personalized LLM for Generating Customized Responses to the Same Query from Different Users cites this paper.

Personalized LLM for Generating Customized Responses to the Same Query from Different Users A Survey on In-context Learning

Reference 10

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source=pdf_text observed=2026-08-11T14:44:36.939142Z digest=sha256:3348d7184da3dba0b7b109af9e0d35fe07279258714ca015da9567dac4ca579c

Observation 4c032626-20c7-4c0b-96d7-527396346fbd · inbound

PICLe: Pseudo-Annotations for In-Context Learning in Low-Resource Named Entity Detection cites this paper.

PICLe: Pseudo-Annotations for In-Context Learning in Low-Resource Named Entity Detection A Survey on In-context Learning

Reference 5

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source=arxiv_source observed=2026-08-11T14:31:07.090475Z digest=sha256:80b6414bbb2c71f6bd84897f8d00bb6093daf0bd8f2ebe62f9b9ab94bad11522

Observation ac6612c4-4ffe-4203-8a67-e8ca06ad1607 · inbound

What Makes In-context Learning Effective for Mathematical Reasoning: A Theoretical Analysis cites this paper.

What Makes In-context Learning Effective for Mathematical Reasoning: A Theoretical Analysis A Survey on In-context Learning

Reference 13

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source=arxiv_source observed=2026-08-11T18:05:21.501309Z digest=sha256:6004c9149ec094803413b80292765e853ed116ce2951814cacf6d6ffc6e4eb19

Observation 1a37ae31-621b-4011-984d-e0dddb8926e0 · inbound

Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations Generation cites this paper.

Greek2MathTex: A Greek Speech-to-Text Framework for LaTeX Equations Generation A Survey on In-context Learning

Reference 2023

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source=pdf_text observed=2026-08-11T17:35:50.681543Z digest=sha256:9856c4d9d67f93a5911e0837c06616ee33cc2de1444fe31e54539e1a6575872b

Observation 44f46ccc-56e5-469a-ab97-7fc3f3e35a1e · inbound

LogBabylon: A Unified Framework for Cross-Log File Integration and Analysis cites this paper.

LogBabylon: A Unified Framework for Cross-Log File Integration and Analysis A Survey on In-context Learning

Reference 4

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source=pdf_text observed=2026-08-11T14:11:44.387497Z digest=sha256:68a37a0752189dd24873593a5094c293904ba95eb750f3a1f32a6299e10ccd4d

Observation 602b00e1-e1c5-4482-b6f8-c30821742914 · inbound

MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning cites this paper.

MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning A Survey on In-context Learning

Reference 8

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source=arxiv_source observed=2026-08-11T13:58:20.363982Z digest=sha256:d83e799561671fa857dcaf9492716d6c8b6ce41cbec6b4572e638d07dc44bf75

Observation c9aff5bf-7acd-4985-ae2b-a60ba4c54b69 · inbound

Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges cites this paper.

Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges A Survey on In-context Learning

Reference 16

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local_arxiv, observed 2026-05-23T07:05:29.085581Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-23T07:05:16.608690Z digest=sha256:a1bf3fd78eee75ab31b56be5e10524c931839449a76ead4d6bfdf6aff8c4668e

Observation 9281ca5a-b0d0-4a1a-8e19-e462286831d4 · inbound

Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health cites this paper.

Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health A Survey on In-context Learning

Reference 23

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source=arxiv_source observed=2026-08-11T13:35:19.787971Z digest=sha256:2c77fc6aec41110e4b74268be6d347dba78a0d463841ae277099db14364a8faf

Observation 8fb01632-41fd-4004-a79e-40339e55b135 · inbound

In-context learning for medical image segmentation cites this paper.

In-context learning for medical image segmentation A Survey on In-context Learning

Reference 30

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source=pdf_text observed=2026-08-11T13:18:09.757916Z digest=sha256:efba9023fe7f2dad9ddd333dfb04f0732ec57633448f09a89d9b30e12114d38d

Observation 0b00c21b-9766-4c57-a512-443dfce64f4b · inbound

Memory-Augmented Agent Training for Business Document Understanding cites this paper.

Memory-Augmented Agent Training for Business Document Understanding A Survey on In-context Learning

Reference 8

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source=arxiv_source observed=2026-08-11T13:27:31.927198Z digest=sha256:bbfb9a8f026688d8d10ff6f76763fc53aee74218eacd5345c52f5f755949e67f

Observation 831a23b3-56f0-4354-bd1b-d0cf91a58f0e · inbound

SYMPHONY: Improving Memory Management for LLM Inference Workloads cites this paper.

SYMPHONY: Improving Memory Management for LLM Inference Workloads A Survey on In-context Learning

Reference 6

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source=pdf_text observed=2026-08-11T10:39:11.542934Z digest=sha256:23623c0e4a445da6a54855231ba691c54315c32be1dc7083ac3f7f677537c449

Observation c89a5a3d-12e8-4c21-a02e-40722e4ed2a4 · inbound

Revisiting In-Context Learning with Long Context Language Models cites this paper.

Revisiting In-Context Learning with Long Context Language Models A Survey on In-context Learning

Reference 8

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source=arxiv_source observed=2026-08-11T06:01:48.926392Z digest=sha256:abd564e37aa012b9f84bb6e610afd697fda6dbd7888ec8e4fb80ae6909940e15

Observation ec07b667-a7a2-4274-aaae-d1501f94de2b · inbound

Reversed Attention: On The Gradient Descent Of Attention Layers In GPT cites this paper.

Reversed Attention: On The Gradient Descent Of Attention Layers In GPT A Survey on In-context Learning

Reference 7

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source=arxiv_source observed=2026-08-11T06:00:38.649207Z digest=sha256:cd5c0351c2a59e5e76cd12026c5281e82d66a73bc0a6f63af353ad3607aab70f

Observation 192e3e35-eedb-495e-876c-045fd16c0ce8 · inbound

A Dual-Perspective Metaphor Detection Framework Using Large Language Models cites this paper.

A Dual-Perspective Metaphor Detection Framework Using Large Language Models A Survey on In-context Learning

Reference 25

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source=pdf_text observed=2026-08-11T05:38:33.752504Z digest=sha256:25c2284cf71bb6b17ac8fcc10e086a239f832b15fee4d4e935db75c3f7542e5a

Observation 9c5e1083-4aac-4edb-95fa-e350312cd85c · inbound

ChatGarment: Garment Estimation, Generation and Editing via Large Language Models cites this paper.

ChatGarment: Garment Estimation, Generation and Editing via Large Language Models A Survey on In-context Learning

Reference 10

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source=pdf_text observed=2026-08-11T05:13:16.371458Z digest=sha256:6040b615cbc676bc57515d85260ec34c69e495e228ecc38a0a861b5d741cd05b

Observation 080b2f7b-1744-406f-a788-f7b1da2c00c4 · inbound

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON cites this paper.

A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON A Survey on In-context Learning

Reference 4

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source=arxiv_source observed=2026-08-11T05:11:32.394604Z digest=sha256:e1f92a68ec40f33b8aff54c7b3b032b737b209476213ccf805d75e5cce50c854

Observation 28de6a46-2707-44f5-bc63-8cca6f1bc8da · inbound

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases cites this paper.

Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases A Survey on In-context Learning

Reference 17

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source=arxiv_source observed=2026-08-11T04:54:11.389489Z digest=sha256:da6a2acae0d544f55650d6919c3232f34858b09aa681026ab42ce37ad3e28ebe

Observation 5d98913d-cb37-4594-b764-ac87293184d3 · inbound

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey cites this paper.

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey A Survey on In-context Learning

Reference 94

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source=pdf_text observed=2026-08-11T14:59:01.542017Z digest=sha256:3d585bd72036b83e12317973f9110b37bed3b484b46d4e56ec0066aedade7d48

Observation 191ba12b-b77a-441c-9c54-0c234096716b · inbound

From Hallucinations to Facts: Enhancing Language Models with Curated Knowledge Graphs cites this paper.

From Hallucinations to Facts: Enhancing Language Models with Curated Knowledge Graphs A Survey on In-context Learning

Reference 10

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source=arxiv_source observed=2026-08-11T04:38:36.687268Z digest=sha256:9070413a9879a5294da6c7bd300d9f5fc2c3e926a7abdfa204de357d0b19833b

Observation acc7ae29-8f32-4a6d-9ae1-3d5196ab5ecc · inbound

A theory of appropriateness with applications to generative artificial intelligence cites this paper.

A theory of appropriateness with applications to generative artificial intelligence A Survey on In-context Learning

Reference 2024

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source=pdf_text observed=2026-08-11T01:04:06.471544Z digest=sha256:90d78e695e197549b2198ad952ef293004a313755203175aa2a748b27c51304b

Observation c589e680-29ae-4819-be01-66472cb732ac · inbound

Find the Intention of Instruction: Comprehensive Evaluation of Instruction Understanding for Large Language Models cites this paper.

Find the Intention of Instruction: Comprehensive Evaluation of Instruction Understanding for Large Language Models A Survey on In-context Learning

Reference 9

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source=arxiv_source observed=2026-08-11T00:39:45.660824Z digest=sha256:cc8754d2eb19c138f8ea9be2221a87970d3461ebb61f471b9f87fd7b06675906

Observation 59e06256-1301-4f47-ba71-e07c2b8ffa6f · inbound

Hindsight Planner: A Closed-Loop Few-Shot Planner for Embodied Instruction Following cites this paper.

Hindsight Planner: A Closed-Loop Few-Shot Planner for Embodied Instruction Following A Survey on In-context Learning

Reference 11

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source=arxiv_source observed=2026-08-11T00:18:20.255156Z digest=sha256:f4b7bdc3ebee3ea9c55bf09e3b0c6217d3925c083b8e6cbcbaf9be6dd8b27465

Observation 724d3bd4-09d7-4e24-bb75-58682ef8f14b · inbound

Learning Spectral Methods by Transformers cites this paper.

Learning Spectral Methods by Transformers A Survey on In-context Learning

Reference 10

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source=pdf_text observed=2026-08-10T22:36:51.201325Z digest=sha256:a3425b8bef930f7dfa30486d38ff0c1d75e07de24c95683f2d9a4adf45aa550a

Observation 86972085-3bca-4dba-bef7-3091d73162f0 · inbound

Financial Named Entity Recognition: How Far Can LLM Go? cites this paper.

Financial Named Entity Recognition: How Far Can LLM Go? A Survey on In-context Learning

Reference 2022

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source=pdf_text observed=2026-08-10T22:16:29.448770Z digest=sha256:67cfa746bca3330520fe861ff6c8ce21870054ef11bc5c8c72165872d9efab03

Observation cbd20f3a-290b-4af2-aa46-90bb51ae1cdb · inbound

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning cites this paper.

Randomly Sampled Language Reasoning Problems Elucidate Limitations of In-Context Learning A Survey on In-context Learning

Reference 9

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source=pdf_text observed=2026-08-10T22:10:33.879293Z digest=sha256:934db1ebfee7c56d7b52e8b50556d255696561836d0d47c0ba36ae2b379c439b

Observation a8e6be2b-c303-40de-8e3d-7e1c5a38396f · inbound

CoReQA: Uncovering Potentials of Language Models in Code Repository Question Answering cites this paper.

CoReQA: Uncovering Potentials of Language Models in Code Repository Question Answering A Survey on In-context Learning

Reference 36

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source=pdf_text observed=2026-08-10T21:56:46.316345Z digest=sha256:255a31a311b5a5c3433a8625bcf9e58dac98671f956e0ab3b7375b65be412c8d

Observation b725fdff-bfe6-4994-a1fa-d45a8db1766c · inbound

A Survey on Large Language Models with some Insights on their Capabilities and Limitations cites this paper.

A Survey on Large Language Models with some Insights on their Capabilities and Limitations A Survey on In-context Learning

Reference 272

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source=pdf_text observed=2026-08-10T22:17:56.449743Z digest=sha256:963e8ca8d91b8fb70f0bceeddb38770621ecefd2028870e0806c451c223f003a

Observation 09fc9568-3321-47df-ba1f-808e3a663427 · inbound

A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education cites this paper.

A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education A Survey on In-context Learning

Reference 21

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source=pdf_text observed=2026-08-10T21:20:23.450972Z digest=sha256:441b04c0db8632ec79f1bb3055ee809cc09db01adcb9d59108711293efc24d23

Observation 4edd29a1-2f38-4c60-82dc-9ee72d642c2f · inbound

Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions cites this paper.

Large Language Models, Knowledge Graphs and Search Engines: A Crossroads for Answering Users' Questions A Survey on In-context Learning

Reference 9

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source=pdf_text observed=2026-08-10T20:57:29.001008Z digest=sha256:1e77b739e4e5916cdee4c730d34daa4b1b5cfbd4f9306639dc857dc2b9a64637

Observation e3fbbae8-5a62-4d37-bc94-97b55baa32f8 · inbound

LLMs Model Non-WEIRD Populations: Experiments with Synthetic Cultural Agents cites this paper.

LLMs Model Non-WEIRD Populations: Experiments with Synthetic Cultural Agents A Survey on In-context Learning

Reference 10

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source=pdf_text observed=2026-08-10T20:56:00.460487Z digest=sha256:4600138991687177c634346daade95eef68c32b2502875753e52514f72281c7e

Observation e4e5b030-6e0e-4a2f-8da1-33f1fd14315b · inbound

Large Language Models for Interpretable Mental Health Diagnosis cites this paper.

Large Language Models for Interpretable Mental Health Diagnosis A Survey on In-context Learning

Reference 10

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source=arxiv_source observed=2026-08-10T20:42:41.777523Z digest=sha256:8c86284de80a307c4b1221d1dfd3f730adce6ab2614122bb31134cab4846c0dd

Observation 1e83ceb7-0974-4c07-b220-b9221b4e69cd · inbound

Foundations of Large Language Models cites this paper.

Foundations of Large Language Models A Survey on In-context Learning

Reference 64

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source=arxiv_source observed=2026-08-10T20:14:58.720433Z digest=sha256:39861cd653fba71db224287ed2d424f233304996693908ab2370c4945af7bde3

Observation e97c38b5-a2d8-4d55-b3ec-5e00b195cfce · inbound

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy cites this paper.

A Survey on Responsible LLMs: Inherent Risk, Malicious Use, and Mitigation Strategy A Survey on In-context Learning

Reference 44

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source=pdf_text observed=2026-08-10T20:05:12.103425Z digest=sha256:c5f5a58adb7cfe10aeef63d49daf6d4c51f45c3b5a63e0fd31a51929fcef4877

Observation bc9c2714-7f9f-4c86-b592-4adf1fcbeb73 · inbound

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models cites this paper.

Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models A Survey on In-context Learning

Reference 33

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verified exact
local_arxiv, observed 2026-05-15T21:20:59.233361Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T21:20:59.128986Z digest=sha256:9c762596d03ca9b556851bf8c8153c844431453cc37b2ff97638e57311a6bb49

Observation a069724d-b7b7-4d0d-9904-e30f6f25547b · inbound

Universal Actions for Enhanced Embodied Foundation Models cites this paper.

Universal Actions for Enhanced Embodied Foundation Models A Survey on In-context Learning

Reference 16

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source=pdf_text observed=2026-08-10T19:29:39.724509Z digest=sha256:69aef3b5425f0c2e0a1a46a6571c0361e3ae3f61c81432e67fa0515f84ce8280

Observation 568430ab-122e-450f-8111-17889571633d · inbound

Visual RAG: Expanding MLLM visual knowledge without fine-tuning cites this paper.

Visual RAG: Expanding MLLM visual knowledge without fine-tuning A Survey on In-context Learning

Reference 7

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source=pdf_text observed=2026-08-10T18:59:22.307226Z digest=sha256:a3d9e8bb7b1c97e423a998c580f031bb99be6d8f06bbe15a31d051e12c027db9

Observation 78709109-ff8c-4fa9-a717-337c47368465 · inbound

AdaptiveLog: An Adaptive Log Analysis Framework with the Collaboration of Large and Small Language Model cites this paper.

AdaptiveLog: An Adaptive Log Analysis Framework with the Collaboration of Large and Small Language Model A Survey on In-context Learning

Reference 11

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source=pdf_text observed=2026-08-10T18:49:25.865042Z digest=sha256:cd9a193b1b7afbc280f470f63ae5ca21d0f34cded9453be57ec85292030899f7

Observation b7b8de68-9c36-4735-a782-ee373a704c4e · inbound

Is your LLM trapped in a Mental Set? Investigative study on how mental sets affect the reasoning capabilities of LLMs cites this paper.

Is your LLM trapped in a Mental Set? Investigative study on how mental sets affect the reasoning capabilities of LLMs A Survey on In-context Learning

Reference 8

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source=arxiv_source observed=2026-08-10T17:51:06.895336Z digest=sha256:444756eacc59b07a863aa13c5012796b49bd477d9875415341634c2116bd4bea

Observation 1546857c-aac3-4d70-b3a7-7cc1bead340b · inbound

IC-Cache: Efficient Large Language Model Serving via In-context Caching cites this paper.

IC-Cache: Efficient Large Language Model Serving via In-context Caching A Survey on In-context Learning

Reference 28

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source=pdf_text observed=2026-08-10T16:59:01.284457Z digest=sha256:44c77c1ed0beb97ae0f108444bd974027232f18489efd995a6d27cac9825802f

Observation 5da9f60d-ff73-4e2e-b34a-3adec2ec0f74 · inbound

OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models cites this paper.

OnionEval: An Unified Evaluation of Fact-conflicting Hallucination for Small-Large Language Models A Survey on In-context Learning

Reference 5

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source=pdf_text observed=2026-08-10T16:40:09.344554Z digest=sha256:b05f751797d3dfbf1377a9949e88c516439080188e38414783fffd67189ae26b

Observation 15c9f3d9-0084-4901-bbd6-1c9499e5e9bf · inbound

Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms cites this paper.

Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms A Survey on In-context Learning

Reference 19

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source=arxiv_source observed=2026-08-10T16:25:32.944875Z digest=sha256:1c737847eb7af4c5f641f866e5c600a67ba7b16a51ac4fe52f7aa424266246da

Observation e8ab4448-8dba-46fe-bf6f-5843d1df4e21 · inbound

RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity cites this paper.

RELexED: Retrieval-Enhanced Legal Summarization with Exemplar Diversity A Survey on In-context Learning

Reference 10

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no resolver link, observed 2026-08-10T15:25:30.450585Z

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source=arxiv_source observed=2026-08-10T15:25:30.450585Z digest=sha256:f053f8a0b07cc9b25dcf343b062737ffd1307c04e7d46dbe2670fc79b72ac901

Observation 9b7e4fe6-9649-46d1-9082-0d97b57e1446 · inbound

Investigating the (De)Composition Capabilities of Large Language Models in Natural-to-Formal Language Conversion cites this paper.

Investigating the (De)Composition Capabilities of Large Language Models in Natural-to-Formal Language Conversion A Survey on In-context Learning

Reference 9

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no resolver link, observed 2026-08-10T15:02:24.047591Z

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source=arxiv_source observed=2026-08-10T15:02:24.047591Z digest=sha256:286e4471b3579d7342ffc001240f431489f18bd1e751bdd3b61259a9232f11a5

Observation 28a76051-b21e-4fe2-b7b9-c1b8576223bf · inbound

JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models cites this paper.

JustLogic: A Comprehensive Benchmark for Evaluating Deductive Reasoning in Large Language Models A Survey on In-context Learning

Reference 8

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no resolver link, observed 2026-08-10T15:04:55.554937Z

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source=arxiv_source observed=2026-08-10T15:04:55.554937Z digest=sha256:c9e60dd40abdf0597af3da9c9b6a87c127c66924cee37e752b11d7784afbae25

Observation 8e92d717-5430-4102-8ef7-fbdab288d567 · inbound

Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM cites this paper.

Code Change Intention, Development Artifact and History Vulnerability: Putting Them Together for Vulnerability Fix Detection by LLM A Survey on In-context Learning

Reference 13

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source=pdf_text observed=2026-08-10T14:48:57.454680Z digest=sha256:27c2fb68fa56c1dc39def81d11b6ea8bc8029eb042d52851e3f357654d4afb12

Observation 2f1ccdae-e7b5-4cef-8e8b-f67e4c96942d · inbound

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads cites this paper.

Task-KV: Task-aware KV Cache Optimization via Semantic Differentiation of Attention Heads A Survey on In-context Learning

Reference 1

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source=pdf_text observed=2026-08-10T14:41:04.955353Z digest=sha256:80788b47aa2a6f8ab295f4f328418026eacf95586d318cff10242c32b1536a6b

Observation 41509929-7ed9-459c-ac58-e4eb498f4fd4 · inbound

ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval cites this paper.

ASRank: Zero-Shot Re-Ranking with Answer Scent for Document Retrieval A Survey on In-context Learning

Reference 12

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no resolver link, observed 2026-08-10T14:32:37.880024Z

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source=arxiv_source observed=2026-08-10T14:32:37.880024Z digest=sha256:9ab23a1f8206f0504f9141700cf3b2031345916db40a849b2f0feed72f230a72

Observation 5e8f4222-34b7-4bd6-abb3-b009023d2e35 · inbound

StaICC: Standardized Evaluation for Classification Task in In-context Learning cites this paper.

StaICC: Standardized Evaluation for Classification Task in In-context Learning A Survey on In-context Learning

Reference 21

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source=arxiv_source observed=2026-08-10T14:06:14.224501Z digest=sha256:4a49af3cea77005f8e454ba749080cb101b64b9fea665b3bcb61cc9be2aa2d59

Observation 5b53538b-465e-49a6-91a9-e0d8ed1fce36 · inbound

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design cites this paper.

GraphICL: Unlocking Graph Learning Potential in LLMs through Structured Prompt Design A Survey on In-context Learning

Reference 10

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no resolver link, observed 2026-08-10T14:01:38.295724Z

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source=arxiv_source observed=2026-08-10T14:01:38.295724Z digest=sha256:0bd0af51b416b665e209d43e1a90496baf291d5499c25b909a8a1823770c0d00

Observation 3c0d7f31-9128-4f76-979c-9c6bc7143aa5 · inbound

SampleLLM: Optimizing Tabular Data Synthesis in Recommendations cites this paper.

SampleLLM: Optimizing Tabular Data Synthesis in Recommendations A Survey on In-context Learning

Reference 9

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no resolver link, observed 2026-08-10T13:48:50.080827Z

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source=pdf_text observed=2026-08-10T13:48:50.080827Z digest=sha256:c70862627df59eee48a592d2f610b6f909db21efb0376d79c9dd13b5f858399a

Observation 67b46f08-62e8-4b23-a2d1-86c7ff491c51 · inbound

Can Transformers Learn Full Bayesian Inference in Context? cites this paper.

Can Transformers Learn Full Bayesian Inference in Context? A Survey on In-context Learning

Reference 23

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source=arxiv_source observed=2026-08-10T10:30:36.042949Z digest=sha256:f21f3f9ce0ec78dac5aa15a132ed34e6c2dcd921fb6d09bf8dea06d0d2b77c86

Observation 73079c1e-86f0-41f8-b8c7-81342ca4022f · inbound

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing cites this paper.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing A Survey on In-context Learning

Reference 12

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source=arxiv_source observed=2026-08-09T18:26:56.015569Z digest=sha256:f8c913e3d0e0658469bd3260f30c300022b9e1ceda46d3ca833ba2c4c5a09b1e

Observation fab1fab7-ad3b-4743-8452-af6cf8b2c564 · inbound

Probing Large Language Models in Reasoning and Translating Complex Linguistic Puzzles cites this paper.

Probing Large Language Models in Reasoning and Translating Complex Linguistic Puzzles A Survey on In-context Learning

Reference 7

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source=arxiv_source observed=2026-08-09T17:40:02.137551Z digest=sha256:99d5d15adc7cd363da7560cbb8c93da3d07fce2cb5e74185c2752bc48d3f9dd5

Observation d8c1cc37-2c43-43b7-9192-9b88cd4f6c80 · inbound

Classic4Children: Adapting Chinese Literary Classics for Children with Large Language Model cites this paper.

Classic4Children: Adapting Chinese Literary Classics for Children with Large Language Model A Survey on In-context Learning

Reference 8

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no resolver link, observed 2026-08-09T16:42:21.234856Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-09T16:42:21.234856Z digest=sha256:9e4a47e0bef7787b6732d3093ca0cde28a1521181b1cf676832228cb61fbd430