Paper Citation Record · LEDGER

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing

As of 10 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2502.00602.

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

pith.paper-citation-record.v1
2502.00602 v2

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:26:56.446574Z

measured 65 of 65 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:34:43.970506Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T12:34:47.754484Z

Reference resolution

64 of 64 outbound references displayed

verified exact3
verified fuzzy8
unresolved53
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ddea3436-633f-4e0e-b2a6-df699d930684 · outbound

This paper cites A neural probabilistic language model.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing A neural probabilistic language model

Reference 1

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Source-reported events for the cited work

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Observation 078661a8-bfce-4497-950d-a85935eda788 · outbound

This paper cites Pattern recognition and machine learning, volume 4.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Pattern recognition and machine learning, volume 4

Reference 2

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Observation ba286dd8-5a3d-467a-bc63-c0a8ce602f07 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing On the Opportunities and Risks of Foundation Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.941132Z

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Observation 81756c13-7e9c-40ed-bd22-e1085a7f593e · outbound

This paper cites Language models are few-shot learners.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Language models are few-shot learners

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.951441Z

Source-reported events for the cited work

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Observation 29e9174a-e7ae-4a99-99e8-a35fa1d0e0b4 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.957742Z

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Observation f3eeec36-cf1f-4a5b-ae2f-b358c1d751f0 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.964047Z

Source-reported events for the cited work

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Observation 7ae62e6f-339a-4f62-94d4-4e52a7bcd39a · outbound

This paper cites Evaluating the ripple effects of knowledge editing in language models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Evaluating the ripple effects of knowledge editing in language models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:58.211400Z

Source-reported events for the cited work

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Observation 1464037b-690c-4166-b4d9-0b2bbea1218a · outbound

This paper cites Elements of information theory.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Elements of information theory

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.982618Z

Source-reported events for the cited work

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Observation a3bce83e-7c9f-4d1a-9f4e-0968102593df · outbound

This paper cites Knowledge Neurons in Pretrained Transformers.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Knowledge Neurons in Pretrained Transformers

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:55.989243Z

Source-reported events for the cited work

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Observation 84ceff7d-93fd-4436-9d34-709d63edfe5e · outbound

This paper cites Editing Factual Knowledge in Language Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Editing Factual Knowledge in Language Models

Reference 10

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Source-reported events for the cited work

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Observation da02cd86-2722-4146-88f3-690889a32de8 · outbound

This paper cites Calibrating Factual Knowledge in Pretrained Language Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Calibrating Factual Knowledge in Pretrained Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.009198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites A Survey on In-context Learning.

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

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.015569Z

Source-reported events for the cited work

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Observation 7f8a3aab-b197-4cdd-931f-178b98ece498 · outbound

This paper cites The Llama 3 Herd of Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing The Llama 3 Herd of Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.021780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb2914bf-a048-4f64-87ac-d609bee73200 · outbound

This paper cites ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.028321Z

Source-reported events for the cited work

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Observation 6655497d-0ecd-452c-b6fd-66c1fef5200d · outbound

This paper cites Aging with grace: Lifelong model editing with discrete key-value adaptors.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Aging with grace: Lifelong model editing with discrete key-value adaptors

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:58.173894Z

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.

Observation fb92d708-92b7-4287-9518-96b09df24047 · outbound

This paper cites Truncation Sampling as Language Model Desmoothing.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Truncation Sampling as Language Model Desmoothing

Reference 16

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Source-reported events for the cited work

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Observation 2204d177-fce7-443a-b638-7d6af2a8474d · outbound

This paper cites Long short-term memory.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Long short-term memory

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.054201Z

Source-reported events for the cited work

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Observation 5f4547cb-941a-4dbc-a830-c37a5db7b4a2 · outbound

This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b3f2b99-773d-4efa-bd06-94c05804d655 · outbound

This paper cites Transformer-Patcher: One Mistake worth One Neuron.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Transformer-Patcher: One Mistake worth One Neuron

Reference 19

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Source-reported events for the cited work

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Observation 4b2ee85d-a69d-42a5-b0ae-e3c27455eb83 · outbound

This paper cites Survey of hallucination in natural language generation.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Survey of hallucination in natural language generation

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b9ffcaa-33ef-41a6-88db-92a5551479ab · outbound

This paper cites Learning to Edit: Aligning LLMs with Knowledge Editing.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Learning to Edit: Aligning LLMs with Knowledge Editing

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.080612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2b0342-b4ae-4b42-8ede-1a26b2746cdc · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Understanding black-box predictions via influence functions

Reference 22

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Source-reported events for the cited work

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Observation 288acc03-3efc-43fe-a696-161161195d9d · outbound

This paper cites Large language models are zero-shot reasoners.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Large language models are zero-shot reasoners

Reference 23

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Source-reported events for the cited work

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Observation e3096a34-2940-4966-8719-5665c0c30af3 · outbound

This paper cites Professor Forcing: A New Algorithm for Training Recurrent Networks.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Professor Forcing: A New Algorithm for Training Recurrent Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.104597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c0423eb-b3ae-4650-9025-d2c75da7f966 · outbound

This paper cites Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Adaptive Label Smoothing with Self-Knowledge in Natural Language Generation

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-09T18:26:57.292112Z

Source-reported events for the cited work

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Observation 18a498a9-1b16-4f90-8455-48dbcefaecdb · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.117440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 291f52ab-e6df-46de-a3a3-c9871687ee6d · outbound

This paper cites Locating and editing factual associations in gpt.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Locating and editing factual associations in gpt

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.124484Z

Source-reported events for the cited work

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Observation 64bae0d1-053e-4957-9f69-bcdd2271f538 · outbound

This paper cites Mass-Editing Memory in a Transformer.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Mass-Editing Memory in a Transformer

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aefd6953-e1e7-4aee-9947-c8ccff503e5c · outbound

This paper cites Fast Model Editing at Scale.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Fast Model Editing at Scale

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.139474Z

Source-reported events for the cited work

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Observation ad76e627-7940-4aba-9845-9ca38931f369 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Memory-based model editing at scale

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:58.063878Z

Source-reported events for the cited work

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Observation 3aec5a26-c1d7-4138-89b5-8bc7eb60ac79 · outbound

This paper cites When does label smoothing help? Advances in neural information processing systems, 32, 2019.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing When does label smoothing help? Advances in neural information processing systems, 32, 2019

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:58.039521Z

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.

Observation f9d0b7c9-78d6-4610-9c6e-2a69649b669f · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Training language models to follow instructions with human feedback

Reference 32

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Source-reported events for the cited work

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Observation f2878f8a-c7a3-423e-866a-899e9e9d7c51 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Language models are unsupervised multitask learners

Reference 33

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Observation 7f8155a4-cc06-493f-bcf4-6ec5dfc957a1 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Direct preference optimization: Your language model is secretly a reward model

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.187968Z

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Observation a93c5575-3a6e-4c6b-81c6-b1832fe3b571 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 35

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Observation ffda8ba5-100f-4c9d-ae08-1b83f1ac6123 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Knowledge Editing in Language Models via Adapted Direct Preference Optimization

Reference 36

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Observation c86e1b7e-70b0-44c1-84e5-5b4aa4ce6073 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Do Massively Pretrained Language Models Make Better Storytellers?

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-08-09T18:26:57.133668Z

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Observation a31c7010-11aa-4f31-af75-1e33f3c6f5dc · outbound

This paper cites Sequence to Sequence Learning with Neural Networks.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Sequence to Sequence Learning with Neural Networks

Reference 38

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Observation 44abd8b6-acdd-4147-8261-12f0214518f9 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Rethinking the inception architecture for computer vision

Reference 39

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Source-reported events for the cited work

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Observation 72ffb4d0-3558-4913-bfb7-165291b11dda · outbound

This paper cites Top-$n\sigma$: Not All Logits Are You Need.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Top-$n\sigma$: Not All Logits Are You Need

Reference 40

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Observation 7ef1a219-a826-41f6-b39f-721b7b634f61 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

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Observation f088568f-0dda-40dc-b9a6-a38ca9946bba · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Attention is all you need

Reference 42

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Observation 3dd24a00-f392-4c90-a37f-a66f048efb4d · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Beyond reverse KL : Generalizing direct preference optimization with diverse divergence constraints

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:57.781716Z

Source-reported events for the cited work

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Observation d3673c36-b155-43a3-a7ac-b846dc343f53 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Making Large Language Models Better Reasoners with Alignment

Reference 44

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Source-reported events for the cited work

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Observation dbdbd37d-a875-4f37-8fdf-149b2572d569 · outbound

This paper cites WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing WISE: Rethinking the Knowledge Memory for Lifelong Model Editing of Large Language Models

Reference 45

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Observation b9d15102-87f5-49f6-8f4c-1e81953a15ec · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models

Reference 46

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Knowledge Editing for Large Language Models: A Survey

Reference 47

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Source-reported events for the cited work

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Observation 035aec74-33e3-4e82-a1e8-d60a72466475 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing DeepEdit: Knowledge Editing as Decoding with Constraints

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.299568Z

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Observation fc2dde73-c9f1-4776-ae94-ac73ede65bdb · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Chain-of-thought prompting elicits reasoning in large language models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.307652Z

Source-reported events for the cited work

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Observation 1a4c97d8-9de6-4984-8dca-5f243266f245 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Stable Knowledge Editing in Large Language Models

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-09T18:26:56.868753Z

Source-reported events for the cited work

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Observation 97747534-0bae-46b2-a44d-5a944e427d08 · outbound

This paper cites DocTER: Evaluating Document-based Knowledge Editing.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing DocTER: Evaluating Document-based Knowledge Editing

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.324733Z

Source-reported events for the cited work

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Observation 3a4b1975-099b-403f-b3f6-dd201f5da4e3 · outbound

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Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing On early stopping in gradient descent learning

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:57.740740Z

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.

Observation 8e49f47a-7002-4faf-a188-9d5c1d5acbde · outbound

This paper cites Editing Large Language Models: Problems, Methods, and Opportunities.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Editing Large Language Models: Problems, Methods, and Opportunities

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.340971Z

Source-reported events for the cited work

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Observation 22b9ae43-f800-4f61-9592-6b9c930a038f · outbound

This paper cites Melo: Enhancing model editing with neuron-indexed dynamic lora.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Melo: Enhancing model editing with neuron-indexed dynamic lora

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:26:57.719476Z

Source-reported events for the cited work

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Observation 88f435bb-d08e-4a64-9aa3-4da4f8ea247b · outbound

This paper cites Uncovering Overfitting in Large Language Model Editing.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Uncovering Overfitting in Large Language Model Editing

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.356054Z

Source-reported events for the cited work

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Observation f0bb1929-c95e-4343-9de2-610b5fcc3995 · outbound

This paper cites InstructEdit: Instruction-based Knowledge Editing for Large Language Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing InstructEdit: Instruction-based Knowledge Editing for Large Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.362331Z

Source-reported events for the cited work

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Observation 1fd3d8df-cf8b-4622-860b-5ea3e2833cb3 · outbound

This paper cites A Comprehensive Study of Knowledge Editing for Large Language Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing A Comprehensive Study of Knowledge Editing for Large Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.372616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 964594c3-526f-4090-af0e-fb11b1b9a7f9 · outbound

This paper cites Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.384264Z

Source-reported events for the cited work

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Observation c4bba2d9-b4be-4a33-b465-fed4a0a72dae · outbound

This paper cites Self-distillation as instance-specific label smoothing.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Self-distillation as instance-specific label smoothing

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.406747Z

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Observation 1055e602-e0a2-4bf2-8cfc-7c7be6c127af · outbound

This paper cites Can We Edit Factual Knowledge by In-Context Learning?.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Can We Edit Factual Knowledge by In-Context Learning?

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.413597Z

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Observation 162c339c-90f4-4f6c-ac81-d3c296bdec1c · outbound

This paper cites MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.424341Z

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Observation 5ed2808a-0148-4403-8ec7-d1902e08bdad · outbound

This paper cites A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.431156Z

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Observation dd1a85f2-4549-4dce-a928-a0a64c61519f · outbound

This paper cites Modifying Memories in Transformer Models.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing Modifying Memories in Transformer Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.438382Z

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Observation 2a16fbfe-5d10-4b3e-a65e-4f9785d50112 · outbound

This paper cites write newline.

Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing write newline

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-09T18:26:56.446574Z

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Pith citing papers

Observation 496d7cfd-03fe-4e65-9dff-11f962fc3063 · inbound

ScienceMeter: Tracking Scientific Knowledge Updates in Language Models cites this paper.

ScienceMeter: Tracking Scientific Knowledge Updates in Language Models Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:34:47.862614Z

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