Paper Citation Record · LEDGER

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

As of 19 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 4 inbound Pith citation observations for arXiv:2411.15102.

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

pith.paper-citation-record.v1
2411.15102 v3

Coverage vector

measured 66 of 66 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:35:57.180894Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:33:46.263379Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:16:57.647582Z

Reference resolution

66 of 66 outbound references displayed

verified exact3
verified fuzzy22
unresolved41
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 53e04610-d988-4489-b46a-594bec087bb9 · outbound

This paper cites write newline.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution write newline

Reference 1

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Source-reported events for the cited work

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Observation 6ba14f4a-3b78-40ad-b1d6-9f8e58db72ec · outbound

This paper cites A Survey on Data Selection for Language Models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution A Survey on Data Selection for Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.662157Z

Source-reported events for the cited work

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Observation c4437a5f-218f-44ee-bc9f-3254a8608198 · outbound

This paper cites Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data

Reference 3

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Source-reported events for the cited work

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Observation 1b44e599-efae-43a8-993c-e3b223148af2 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 4

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Source-reported events for the cited work

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Observation 9b4d7b84-71fe-4439-b2d8-19b5d380eb67 · outbound

This paper cites If influence functions are the answer, then what is the question? Advances in Neural Information Processing Systems, 2022.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution If influence functions are the answer, then what is the question? Advances in Neural Information Processing Systems, 2022

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.973082Z

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Observation 621496e3-05eb-4688-acf2-84aeb28f1b5b · outbound

This paper cites Influence functions in deep learning are fragile.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Influence functions in deep learning are fragile

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.939057Z

Source-reported events for the cited work

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Observation ce91db4c-a732-4eac-b2ff-4f4ceb8ee141 · outbound

This paper cites Thread: Circuits.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Thread: Circuits

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.895322Z

Source-reported events for the cited work

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Observation a97ef5ff-8ad5-4b5b-ac33-9ca856e05aa6 · outbound

This paper cites How Do Large Language Models Acquire Factual Knowledge During Pretraining?.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Reference 8

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Observation e2fcadd2-d15f-4de8-ad84-1c786583c60b · outbound

This paper cites Complex claim verification with evidence retrieved in the wild.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Complex claim verification with evidence retrieved in the wild

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.861265Z

Source-reported events for the cited work

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Observation b9165765-447f-4720-9814-63c984db6434 · outbound

This paper cites What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.730681Z

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Observation 885ebea6-fa67-483e-a71c-60ab5588f4aa · outbound

This paper cites ContextCite: Attributing Model Generation to Context.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution ContextCite: Attributing Model Generation to Context

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.740603Z

Source-reported events for the cited work

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Observation 1702fd33-82f3-4800-9a7d-cfd7e5e632cc · outbound

This paper cites Smith, and Matt Gardner.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Smith, and Matt Gardner

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.838203Z

Source-reported events for the cited work

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Observation ee5e0c4b-39b7-47bc-8ca6-7f45db96445b · outbound

This paper cites The Llama 3 Herd of Models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution The Llama 3 Herd of Models

Reference 13

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Observation ba70c3f0-409b-4a25-90a7-c941605337f5 · outbound

This paper cites Sequential Integrated Gradients: a simple but effective method for explaining language models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Sequential Integrated Gradients: a simple but effective method for explaining language models

Reference 14

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Observation 87b46684-f85a-4a1c-b17d-19a5fde2aabd · outbound

This paper cites RARR : Researching and revising what language models say, using language models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution RARR : Researching and revising what language models say, using language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.817532Z

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Observation 6418f845-e94f-4158-9cff-5f5156a5786e · outbound

This paper cites Enabling Large Language Models to Generate Text with Citations.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Enabling Large Language Models to Generate Text with Citations

Reference 16

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Observation 7162a793-9f5b-45eb-9060-69070782d5ff · outbound

This paper cites Learning to fake it: Limited responses and fabricated references provided by chatgpt for medical questions.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Learning to fake it: Limited responses and fabricated references provided by chatgpt for medical questions

Reference 17

Resolution: verified exact; doi, observed 2026-08-12T14:35:57.270798Z

Source-reported events for the cited work

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Observation 020c4696-1f56-416f-8c7e-0674163428d2 · outbound

This paper cites Studying Large Language Model Generalization with Influence Functions.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Studying Large Language Model Generalization with Influence Functions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.799968Z

Source-reported events for the cited work

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Observation 17510f07-1ef2-407d-ab8c-79a6c9ea3a9a · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.808789Z

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Observation 1546b918-24d8-4338-920a-934621c3a129 · outbound

This paper cites Training Compute-Optimal Large Language Models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Training Compute-Optimal Large Language Models

Reference 20

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Observation 66be7902-0580-4390-8139-6ea6e138dd3e · outbound

This paper cites Retrieving supporting evidence for generative question answering.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Retrieving supporting evidence for generative question answering

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.798561Z

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Observation 7e73fbd9-8e30-4a05-b729-e28c9661f56a · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Unresolved cited work

Reference 22

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Observation f675a1e2-46bf-4ff5-a3db-3966a5e97731 · outbound

This paper cites Large language models struggle to learn long-tail knowledge.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Large language models struggle to learn long-tail knowledge

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:56.841429Z

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Observation 5f3a38af-fb4a-44d6-9964-c5a0491e2fd5 · outbound

This paper cites Scaling Laws for Neural Language Models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Scaling Laws for Neural Language Models

Reference 24

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Observation 00f8e26e-d780-4634-9956-29ef216c453f · outbound

This paper cites Understanding Black-box Predictions via Influence Functions.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Understanding Black-box Predictions via Influence Functions

Reference 25

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Observation 79968158-cc59-4002-8267-f88c366eb762 · outbound

This paper cites BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

Reference 26

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Observation 7432d9d0-9697-4dca-baa4-928d8415f0df · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 27

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Observation cd4e48c9-b7e6-4fb9-b0bf-f00b91c6d16f · outbound

This paper cites Improving attributed text generation of large language models via preference learning.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Improving attributed text generation of large language models via preference learning

Reference 28

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Observation 86457418-9281-4eb1-afac-d31d13fa8029 · outbound

This paper cites Visualizing and Understanding Neural Models in NLP.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Visualizing and Understanding Neural Models in NLP

Reference 29

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Observation bfcba844-1f43-43b0-8cab-d553a787d6e7 · outbound

This paper cites Understanding Neural Networks through Representation Erasure.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Understanding Neural Networks through Representation Erasure

Reference 30

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Observation 80f8c8d4-2158-4477-8faa-5bbf6709d005 · outbound

This paper cites LL atrieval: LLM -verified retrieval for verifiable generation.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution LL atrieval: LLM -verified retrieval for verifiable generation

Reference 31

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Observation 8afa6bf8-66d8-4a00-96cc-80a67853e2f3 · outbound

This paper cites Evaluating Verifiability in Generative Search Engines.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Evaluating Verifiability in Generative Search Engines

Reference 32

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This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 33

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Observation 9e0a528a-ec79-418e-bc23-e4334f9f4aab · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution A Unified Approach to Interpreting Model Predictions

Reference 34

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This paper cites Manning, Prabhakar Raghavan, and Hinrich Sch\" u tze.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Manning, Prabhakar Raghavan, and Hinrich Sch\" u tze

Reference 35

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Observation 0850fdb7-aa72-4a1d-96bd-ce27dd428f85 · outbound

This paper cites The Natural Language Decathlon: Multitask Learning as Question Answering.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution The Natural Language Decathlon: Multitask Learning as Question Answering

Reference 36

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Observation 6b9da4f2-ee22-4cba-ac7b-771f0221a466 · outbound

This paper cites Teaching language models to support answers with verified quotes.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Teaching language models to support answers with verified quotes

Reference 37

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This paper cites Exploring the role of BERT token representations to explain sentence probing results.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Exploring the role of BERT token representations to explain sentence probing results

Reference 38

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution WebGPT: Browser-assisted question-answering with human feedback

Reference 39

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution GPT-4 Technical Report

Reference 40

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This paper cites Credible without credit: Domain experts assess generative language models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Credible without credit: Domain experts assess generative language models

Reference 41

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Efficiently Scaling Transformer Inference

Reference 42

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Unresolved cited work

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This paper cites Estimating training data influence by tracing gradient descent.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Estimating training data influence by tracing gradient descent

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.535232Z

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Observation 21b57263-992e-42e1-b2aa-87fc4f8e3fe5 · outbound

This paper cites Know what you don ' t know: Unanswerable questions for SQ u AD.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Know what you don ' t know: Unanswerable questions for SQ u AD

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.515053Z

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Observation 85b3b081-28ba-43db-8f2e-d182c8fffa23 · outbound

This paper cites Impact of pretraining term frequencies on few-shot numerical reasoning.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Impact of pretraining term frequencies on few-shot numerical reasoning

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.498341Z

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Observation e85b7631-15b5-41b6-b3f7-c649ba476fea · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Sentence-bert: Sentence embeddings using siamese bert-networks

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.476108Z

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Observation 66104c41-9473-4eeb-b75a-4af82136899e · outbound

This paper cites "Why Should I Trust You?": Explaining the Predictions of Any Classifier.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution "Why Should I Trust You?": Explaining the Predictions of Any Classifier

Reference 48

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Observation b90edd80-704e-4350-8cd9-93f9b7a0ec00 · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Percentage points for a generalized esd many-outlier procedure

Reference 49

Resolution: verified exact; raw_fallback, observed 2026-08-12T14:35:57.679509Z

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Observation fe4aeb78-cd3e-4246-818a-38b6e5e38703 · outbound

This paper cites Discretized integrated gradients for explaining language models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Discretized integrated gradients for explaining language models

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.455344Z

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Observation 514e84e7-ff44-4e59-89d5-f16645fa73ce · outbound

This paper cites Is Attention Interpretable?.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Is Attention Interpretable?

Reference 51

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This paper cites Integrated directional gradients: Feature interaction attribution for neural NLP models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Integrated directional gradients: Feature interaction attribution for neural NLP models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.434834Z

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Observation 037978e8-d9a4-4de2-a24e-b507ac452071 · outbound

This paper cites Towards Verifiable Text Generation with Evolving Memory and Self-Reflection.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Towards Verifiable Text Generation with Evolving Memory and Self-Reflection

Reference 53

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Observation a8c07973-1e5c-4370-8d8b-6a52d7dd7ce5 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Gemini: A Family of Highly Capable Multimodal Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.082725Z

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This paper cites LaMDA: Language Models for Dialog Applications.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution LaMDA: Language Models for Dialog Applications

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.088116Z

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Attention Is All You Need

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.094872Z

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution `` according to

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.411479Z

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This paper cites Attention is not not explanation.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Attention is not not explanation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.389329Z

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Observation b891457e-ec68-4df3-a50b-ecd23b942b88 · outbound

This paper cites Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Perturbed Masking: Parameter-free Probing for Analyzing and Interpreting BERT

Reference 59

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Observation 5a8bb4a0-d0c4-4af4-a368-05c1cbb6d183 · outbound

This paper cites Qwen2 Technical Report.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Qwen2 Technical Report

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.128678Z

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This paper cites Cohen, Ruslan Salakhutdinov, and Christopher D.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Cohen, Ruslan Salakhutdinov, and Christopher D

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.138158Z

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Interpreting Language Models with Contrastive Explanations

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.144257Z

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Observation d1ee1281-8713-420b-a23f-085ed1736d0e · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Chatgpt hallucinates when attributing answers

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:35:58.340626Z

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Observation 35fba0f7-d3cc-4cf4-a4d2-24ceb33819df · outbound

This paper cites @esa (Ref.

AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution @esa (Ref

Reference 64

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Observation c88faba7-656e-4a99-8dc7-1ce9675d72af · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution Unresolved cited work

Reference 65

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Observation cff3876c-63ed-462b-88d5-3e1a6014a0fd · outbound

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AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution tab:theoretical_flops table

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T14:35:57.180894Z

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Pith citing papers

Observation 2510c1a9-8587-4c44-8941-b59d435aa1a6 · inbound

Know Or Not: a library for evaluating out-of-knowledge base robustness cites this paper.

Know Or Not: a library for evaluating out-of-knowledge base robustness AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-15T20:33:46.263379Z

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Observation b79a54e8-234a-45cf-8d40-d9ec911f0aba · inbound

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning cites this paper.

TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

Reference 6

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In-Context Credit Assignment via the Core cites this paper.

In-Context Credit Assignment via the Core AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:56.881577Z

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Observation afa32f5e-3908-4c27-8e09-71b88d0bca83 · inbound

RREDCoT: Segment-Level Reward Redistribution for Reasoning Models cites this paper.

RREDCoT: Segment-Level Reward Redistribution for Reasoning Models AttriBoT: A Bag of Tricks for Efficiently Approximating Leave-One-Out Context Attribution

Reference 139

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:16:57.648842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.