Paper Citation Record · LEDGER

Tool Unlearning for Tool-Augmented LLMs

As of 23 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 5 inbound Pith citation observations for arXiv:2502.01083.

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

pith.paper-citation-record.v1
2502.01083 v2

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:44:01.352034Z

measured 82 of 82 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:00:59.292382Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T16:48:02.708528Z

Reference resolution

77 of 77 outbound references displayed

verified exact5
verified fuzzy34
unresolved38
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b474082b-8275-42db-a50f-223af6875b9e · outbound

This paper cites write newline.

Tool Unlearning for Tool-Augmented LLMs write newline

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.276940Z

Source-reported events for the cited work

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Observation 353b3536-07b3-4a49-bf37-33cb2ed1f76a · outbound

This paper cites API - BLEND : A comprehensive corpora for training and benchmarking API LLM s.

Tool Unlearning for Tool-Augmented LLMs API - BLEND : A comprehensive corpora for training and benchmarking API LLM s

Reference 2

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Source-reported events for the cited work

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Observation af478818-5ea0-46ff-880c-dd7986b65084 · outbound

This paper cites an unresolved cited work.

Tool Unlearning for Tool-Augmented LLMs Unresolved cited work

Reference 3

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Source-reported events for the cited work

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Observation bc66faa9-0456-41ec-bcec-09d3b1dea570 · outbound

This paper cites and Triantafillou, P.

Tool Unlearning for Tool-Augmented LLMs and Triantafillou, P

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.262498Z

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Observation beb4a90d-13f7-4afb-b1a3-9167ba70bd24 · outbound

This paper cites Membership inference attacks from first principles.

Tool Unlearning for Tool-Augmented LLMs Membership inference attacks from first principles

Reference 5

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Observation c220032b-3bb7-408a-b2ad-14520722fd3d · outbound

This paper cites and Amiri, H.

Tool Unlearning for Tool-Augmented LLMs and Amiri, H

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.256666Z

Source-reported events for the cited work

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Observation d7ef15d6-d672-4443-899e-b01ed2bdfd3f · outbound

This paper cites MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning.

Tool Unlearning for Tool-Augmented LLMs MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning

Reference 7

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Source-reported events for the cited work

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Observation 014f2cd0-549a-4351-89bd-d1a13fd121b9 · outbound

This paper cites Understanding Machine Unlearning Through the Lens of Mode Connectivity.

Tool Unlearning for Tool-Augmented LLMs Understanding Machine Unlearning Through the Lens of Mode Connectivity

Reference 8

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Source-reported events for the cited work

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Observation ea28271b-e69e-4820-a995-26c092f8aa40 · outbound

This paper cites GNND elete: A general strategy for unlearning in graph neural networks.

Tool Unlearning for Tool-Augmented LLMs GNND elete: A general strategy for unlearning in graph neural networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.250279Z

Source-reported events for the cited work

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Observation 4d2d866d-6fb0-4a09-9db2-3306d0635036 · outbound

This paper cites Towards efficient machine unlearning with data augmentation: Guided loss-increasing (gli) to prevent the catastrophic model utility drop.

Tool Unlearning for Tool-Augmented LLMs Towards efficient machine unlearning with data augmentation: Guided loss-increasing (gli) to prevent the catastrophic model utility drop

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.244116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de0b0d3b-da61-48c7-847d-bd713f4f0d0b · outbound

This paper cites S., Tarun, A.

Tool Unlearning for Tool-Augmented LLMs S., Tarun, A

Reference 11

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Source-reported events for the cited work

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Observation 14d8ceab-9ba4-4311-9b85-4fb66a443669 · outbound

This paper cites Evaluating the Ripple Effects of Knowledge Editing in Language Models.

Tool Unlearning for Tool-Augmented LLMs Evaluating the Ripple Effects of Knowledge Editing in Language Models

Reference 12

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Source-reported events for the cited work

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Observation ef5179da-2c07-4853-a459-e4376859e58e · outbound

This paper cites Gpt3.int8(): 8-bit matrix multiplication for transformers at scale.

Tool Unlearning for Tool-Augmented LLMs Gpt3.int8(): 8-bit matrix multiplication for transformers at scale

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.237684Z

Source-reported events for the cited work

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Observation 77ea33fd-f4d8-45ef-a65c-a00f209bbd34 · outbound

This paper cites and Russinovich, M.

Tool Unlearning for Tool-Augmented LLMs and Russinovich, M

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.231522Z

Source-reported events for the cited work

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Observation 02bf04fe-0b19-4aa7-a1c2-da4db8e42a24 · outbound

This paper cites Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation.

Tool Unlearning for Tool-Augmented LLMs Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.224341Z

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Observation 90e3a599-03d6-45b7-bcba-3a1addd568b9 · outbound

This paper cites Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond.

Tool Unlearning for Tool-Augmented LLMs Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond

Reference 16

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Observation d114bf62-2d20-4268-b0cd-e72c15a2a690 · outbound

This paper cites Challenging forgets: Unveiling the worst-case forget sets in machine unlearning.

Tool Unlearning for Tool-Augmented LLMs Challenging forgets: Unveiling the worst-case forget sets in machine unlearning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.216390Z

Source-reported events for the cited work

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Observation e0b591d2-1634-488e-82d2-841df16016a3 · outbound

This paper cites Erasing concepts from diffusion models.

Tool Unlearning for Tool-Augmented LLMs Erasing concepts from diffusion models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.209081Z

Source-reported events for the cited work

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Observation 29eebfe7-6912-4e68-9943-fb59857bb89b · outbound

This paper cites Pal: program-aided language models.

Tool Unlearning for Tool-Augmented LLMs Pal: program-aided language models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.201834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5f6c40da-05f0-46f7-a3b8-69037e171f2b · outbound

This paper cites Eternal sunshine of the spotless net: Selective forgetting in deep networks.

Tool Unlearning for Tool-Augmented LLMs Eternal sunshine of the spotless net: Selective forgetting in deep networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.195007Z

Source-reported events for the cited work

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Observation 4a9142af-4479-4217-a902-0e62fd9b49c0 · outbound

This paper cites Factual or contextual? disentangling error types in entity description generation.

Tool Unlearning for Tool-Augmented LLMs Factual or contextual? disentangling error types in entity description generation

Reference 21

Resolution: verified exact; doi, observed 2026-08-09T16:44:01.415168Z

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Observation 84158d3b-7b9f-4562-9ce1-321770ca2170 · outbound

This paper cites Amnesiac machine learning.

Tool Unlearning for Tool-Augmented LLMs Amnesiac machine learning

Reference 22

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Observation fb114df0-acd8-4aaa-83ad-42f301a861fb · outbound

This paper cites Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue.

Tool Unlearning for Tool-Augmented LLMs Model Editing Harms General Abilities of Large Language Models: Regularization to the Rescue

Reference 23

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Observation 55d74762-f49e-43b6-9eec-c4f5432def50 · outbound

This paper cites Towards a unified view of parameter-efficient transfer learning.

Tool Unlearning for Tool-Augmented LLMs Towards a unified view of parameter-efficient transfer learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.188790Z

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Observation 6ab76271-75a3-451a-ab99-9ab72f4e1e17 · outbound

This paper cites Measuring massive multitask language understanding.

Tool Unlearning for Tool-Augmented LLMs Measuring massive multitask language understanding

Reference 25

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Observation a809ea3e-0785-4fc2-888c-33c132e86c13 · outbound

This paper cites Learn to unlearn for deep neural networks: Minimizing unlearning interference with gradient projection.

Tool Unlearning for Tool-Augmented LLMs Learn to unlearn for deep neural networks: Minimizing unlearning interference with gradient projection

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.178394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 820cad9a-da60-48d1-a339-b721a4a75e7d · outbound

This paper cites J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W.

Tool Unlearning for Tool-Augmented LLMs J., yelong shen, Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W

Reference 27

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Observation 4a06298e-ceae-4196-8be5-9dad6a7ab7f0 · outbound

This paper cites Unlearning or obfuscating? jogging the memory of unlearned LLM s via benign relearning.

Tool Unlearning for Tool-Augmented LLMs Unlearning or obfuscating? jogging the memory of unlearned LLM s via benign relearning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.167734Z

Source-reported events for the cited work

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Observation 86971ada-ebea-4a7b-a2d2-6fe9ce4a3736 · outbound

This paper cites T., Wortsman, M., Schmidt, L., Hajishirzi, H., and Farhadi, A.

Tool Unlearning for Tool-Augmented LLMs T., Wortsman, M., Schmidt, L., Hajishirzi, H., and Farhadi, A

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.161533Z

Source-reported events for the cited work

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Observation 2f7fff57-a5b9-4b42-8b11-0d784fbbab8a · outbound

This paper cites Knowledge unlearning for mitigating privacy risks in language models.

Tool Unlearning for Tool-Augmented LLMs Knowledge unlearning for mitigating privacy risks in language models

Reference 30

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Observation 7187d824-8036-463f-86dc-880087e368ff · outbound

This paper cites Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference.

Tool Unlearning for Tool-Augmented LLMs Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference

Reference 31

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Observation 2b1f0873-2805-426c-982b-a2993fa57036 · outbound

This paper cites Model sparsity can simplify machine unlearning.

Tool Unlearning for Tool-Augmented LLMs Model sparsity can simplify machine unlearning

Reference 32

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Observation 512a1b65-e4ce-4db4-825f-3ee13ee18249 · outbound

This paper cites SOUL : Unlocking the power of second-order optimization for LLM unlearning.

Tool Unlearning for Tool-Augmented LLMs SOUL : Unlocking the power of second-order optimization for LLM unlearning

Reference 33

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Observation ac514c39-7efb-4e84-8b08-c4c7027ab9fd · outbound

This paper cites RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models.

Tool Unlearning for Tool-Augmented LLMs RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models

Reference 34

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Observation 21f7f689-4d4d-4bf9-bb5d-493a36313757 · outbound

This paper cites Preserving privacy through dememorization: An unlearning technique for mitigating memorization risks in language models.

Tool Unlearning for Tool-Augmented LLMs Preserving privacy through dememorization: An unlearning technique for mitigating memorization risks in language models

Reference 35

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This paper cites Ablating concepts in text-to-image diffusion models.

Tool Unlearning for Tool-Augmented LLMs Ablating concepts in text-to-image diffusion models

Reference 36

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Observation 77b62b7c-eb5f-4366-b825-6f87b2d6ae8d · outbound

This paper cites Towards unbounded machine unlearning.

Tool Unlearning for Tool-Augmented LLMs Towards unbounded machine unlearning

Reference 37

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Observation cbaf53f6-0e1a-4735-8316-a7be0954f9a0 · outbound

This paper cites Machine unlearning for image-to-image generative models.

Tool Unlearning for Tool-Augmented LLMs Machine unlearning for image-to-image generative models

Reference 38

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Observation be04c8b1-2a30-4285-9344-3816ff8929c8 · outbound

This paper cites API -bank: A comprehensive benchmark for tool-augmented LLM s.

Tool Unlearning for Tool-Augmented LLMs API -bank: A comprehensive benchmark for tool-augmented LLM s

Reference 39

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Observation 755a4c81-66d4-4669-8353-810efc0806d8 · outbound

This paper cites The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning.

Tool Unlearning for Tool-Augmented LLMs The WMDP Benchmark: Measuring and Reducing Malicious Use With Unlearning

Reference 40

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Observation a3e49628-d215-42a6-8454-50c5fccc6e5c · outbound

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Tool Unlearning for Tool-Augmented LLMs Unresolved cited work

Reference 41

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Observation 421c1e0a-5cf3-4d09-9070-c6541ae6a648 · outbound

This paper cites Muter: Machine unlearning on adversarially trained models.

Tool Unlearning for Tool-Augmented LLMs Muter: Machine unlearning on adversarially trained models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.123072Z

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Observation 6366b184-b445-4bfe-95fa-e5255a288bf0 · outbound

This paper cites An adversarial perspective on machine unlearning for AI safety.

Tool Unlearning for Tool-Augmented LLMs An adversarial perspective on machine unlearning for AI safety

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.115695Z

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Observation 09464478-4391-473e-8841-14bc97c76f50 · outbound

This paper cites Eight Methods to Evaluate Robust Unlearning in LLMs.

Tool Unlearning for Tool-Augmented LLMs Eight Methods to Evaluate Robust Unlearning in LLMs

Reference 44

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This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

Tool Unlearning for Tool-Augmented LLMs The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 45

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This paper cites C., and Kolter, J.

Tool Unlearning for Tool-Augmented LLMs C., and Kolter, J

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.107837Z

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Observation 24c240d7-8478-4394-8d46-1bd162a16a59 · outbound

This paper cites Training language models to follow instructions with human feedback.

Tool Unlearning for Tool-Augmented LLMs Training language models to follow instructions with human feedback

Reference 47

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Observation 1bbf578c-51e3-4020-a039-bf11e6f9a2de · outbound

This paper cites TALM: Tool Augmented Language Models.

Tool Unlearning for Tool-Augmented LLMs TALM: Tool Augmented Language Models

Reference 48

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Observation 98268bd3-0bb6-46d6-aca1-5e896321e18b · outbound

This paper cites Gorilla: Large Language Model Connected with Massive APIs.

Tool Unlearning for Tool-Augmented LLMs Gorilla: Large Language Model Connected with Massive APIs

Reference 49

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Observation aaf82bc9-0f88-4bbc-8841-50c94a184a83 · outbound

This paper cites In-context unlearning: Language models as few-shot unlearners.

Tool Unlearning for Tool-Augmented LLMs In-context unlearning: Language models as few-shot unlearners

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.092364Z

Source-reported events for the cited work

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Observation 6e39aec6-598d-427c-9aa6-22dc7495e3ac · outbound

This paper cites Tool LLM : Facilitating large language models to master 16000+ real-world API s.

Tool Unlearning for Tool-Augmented LLMs Tool LLM : Facilitating large language models to master 16000+ real-world API s

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.083434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 76b2c46a-2d62-493c-ad9d-329f2133922f · outbound

This paper cites D., Ermon, S., and Finn, C.

Tool Unlearning for Tool-Augmented LLMs D., Ermon, S., and Finn, C

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.074926Z

Source-reported events for the cited work

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Observation 2a62ea5f-f239-48cf-aa7e-04b9e74feb43 · outbound

This paper cites Toolformer: Language models can teach themselves to use tools.

Tool Unlearning for Tool-Augmented LLMs Toolformer: Language models can teach themselves to use tools

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T16:44:02.066594Z

Source-reported events for the cited work

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Observation db7c2962-025e-4419-bf35-77c6af2f4607 · outbound

This paper cites Adversarial unlearning: Reducing confidence along adversarial directions.

Tool Unlearning for Tool-Augmented LLMs Adversarial unlearning: Reducing confidence along adversarial directions

Reference 54

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Tool Unlearning for Tool-Augmented LLMs S., Wei, J., Chung, H

Reference 55

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Tool Unlearning for Tool-Augmented LLMs Exploring the impact of model scaling on parameter-efficient tuning

Reference 56

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Tool Unlearning for Tool-Augmented LLMs W., Chowdhery, A., Le, Q., Chi, E., Zhou, D., and Wei, J

Reference 57

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Tool Unlearning for Tool-Augmented LLMs ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Cases

Reference 58

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Reference 59

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Tool Unlearning for Tool-Augmented LLMs LLaMA: Open and Efficient Foundation Language Models

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Tool Unlearning for Tool-Augmented LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

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Tool Unlearning for Tool-Augmented LLMs A., and Arora, R

Reference 62

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Reference 63

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Tool Unlearning for Tool-Augmented LLMs KGA : A general machine unlearning framework based on knowledge gap alignment

Reference 64

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Tool Unlearning for Tool-Augmented LLMs Shared adversarial unlearning: Backdoor mitigation by unlearning shared adversarial examples

Reference 65

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Tool Unlearning for Tool-Augmented LLMs Knowledge Conflicts for LLMs: A Survey

Reference 66

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Tool Unlearning for Tool-Augmented LLMs Machine unlearning of pre-trained large language models

Reference 67

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Tool Unlearning for Tool-Augmented LLMs Large Language Model Unlearning

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Tool Unlearning for Tool-Augmented LLMs Evaluating large language models at evaluating instruction following

Reference 69

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Tool Unlearning for Tool-Augmented LLMs Towards certified unlearning for deep neural networks

Reference 70

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Tool Unlearning for Tool-Augmented LLMs Negative preference optimization: From catastrophic collapse to effective unlearning

Reference 71

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Tool Unlearning for Tool-Augmented LLMs E., and Stoica, I

Reference 72

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Tool Unlearning for Tool-Augmented LLMs Lima: Less is more for alignment

Reference 73

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Tool Unlearning for Tool-Augmented LLMs Instruction-Following Evaluation for Large Language Models

Reference 74

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Tool Unlearning for Tool-Augmented LLMs @esa (Ref

Reference 75

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Reference 76

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Reference 77

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Pith citing papers

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Speech Unlearning Tool Unlearning for Tool-Augmented LLMs

Reference 32

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Generative Model Unlearning: A Survey through Target Events, Unlearning Operators, and Evaluation Protocols cites this paper.

Generative Model Unlearning: A Survey through Target Events, Unlearning Operators, and Evaluation Protocols Tool Unlearning for Tool-Augmented LLMs

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CURE:Circuit-Aware Unlearning for LLM-based Recommendation Tool Unlearning for Tool-Augmented LLMs

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A Numerical PDEs Approach to Evolution Equations in Shape Analysis Based on Regularized Morphoelasticity cites this paper.

A Numerical PDEs Approach to Evolution Equations in Shape Analysis Based on Regularized Morphoelasticity Tool Unlearning for Tool-Augmented LLMs

Reference 9

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Understanding Machine Unlearning Through the Lens of Mode Connectivity Tool Unlearning for Tool-Augmented LLMs

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