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Paper Citation Record · LEDGER

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2608.01359.

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

pith.paper-citation-record.v1
2608.01359 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:20:40.088199Z

measured 24 of 24 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

  • verified exact4
  • verified fuzzy2
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f9c5233-f1cd-4007-ac5c-5aa324bfcd40 · outbound

This paper cites Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Uncovering Competing Poisoning Attacks in Retrieval-Augmented Generation

Reference 1

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source=pdf_text observed=2026-08-06T00:20:40.017938Z digest=sha256:4a51d1b483d12a5128f0a1785e9a5aee4f8d7d241225cda850469f3ffa60dcce

Observation 0972110d-1a57-4aba-9f44-5e3aaf48fb45 · outbound

This paper cites arXiv:2603.00511.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents arXiv:2603.00511

Reference 3

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source=pdf_text observed=2026-08-06T00:20:40.025963Z digest=sha256:14bb1f5d71693226f8659318c13882e2deda75b6875fe65c2001ba05a054a058

Observation ac901cd2-dad2-4937-a5c2-654d0b4cb675 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 5

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no resolver link, observed 2026-08-06T00:20:40.032201Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:20:40.032201Z digest=sha256:efc3aa2c10f0aca213ed6f146f41d57769e1ff8bf209f16d00a121026692fd05

Observation 11006c9c-6e42-43b3-9a62-91c00dced89c · outbound

This paper cites Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-08-06T00:20:40.450771Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T00:20:40.041332Z digest=sha256:f24405dd89b17f8fd477eab587847b49368052076e173bfec966b7bffa843f57

Observation 2b76b392-f766-448e-8d3e-da9de0ee1909 · outbound

This paper cites PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning

Reference 9

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verified exact
local_arxiv, observed 2026-08-06T00:20:40.435146Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T00:20:40.044174Z digest=sha256:e879864609968aaeabb2379dd688c5aeab4086eb962170b426fc0545e04dd567

Observation 4b4cc81e-8fc1-4c58-9db5-cec3872c2123 · outbound

This paper cites SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning

Reference 10

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verified exact
local_arxiv, observed 2026-08-06T00:20:40.420928Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T00:20:40.048015Z digest=sha256:138d7e5b5fa2938376dca2a787bd47483b5c0b3a64e4083b40650105b2131ebd

Observation 5b2205f5-c232-4c6e-bfcd-424e46e81241 · outbound

This paper cites Qwen2.5 Technical Report.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Qwen2.5 Technical Report

Reference 12

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source=pdf_text observed=2026-08-06T00:20:40.054920Z digest=sha256:2bddeaaeacc83e13bfb8e73eaa3e046d5ff27c5122648d322d385cf47b6efa4a

Observation b1fc7b2f-e1a4-412a-b807-2b656a6d3d58 · outbound

This paper cites arXiv:2505.11277.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents arXiv:2505.11277

Reference 13

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source=pdf_text observed=2026-08-06T00:20:40.057887Z digest=sha256:ce9c59905ef87973ea75b96baf95320e0500c97c8ccac034ace667240226766a

Observation 5e34ed8c-ff10-4a1f-9d75-36923b7fa654 · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 14

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source=pdf_text observed=2026-08-06T00:20:40.060362Z digest=sha256:958042383a10d227c5c387172a177466f978078a0afb804d05051ddaeb67d8ae

Observation 29c8dff4-03fb-4f28-9ed0-400f80cb0be3 · outbound

This paper cites A Survey of On-Policy Distillation for Large Language Models.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents A Survey of On-Policy Distillation for Large Language Models

Reference 15

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source=pdf_text observed=2026-08-06T00:20:40.063048Z digest=sha256:82519df15c79bf89fad652066d3f8988945f4dfdb88a4844de95916d53ff941f

Observation be87197f-f4b6-4920-997e-311f86f801fc · outbound

This paper cites GAPD: Gold-Action Policy Distillation for Agentic Reinforcement Learning in Knowledge Base Question Answering.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents GAPD: Gold-Action Policy Distillation for Agentic Reinforcement Learning in Knowledge Base Question Answering

Reference 16

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local_arxiv, observed 2026-08-06T00:20:40.304160Z

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

source=pdf_text observed=2026-08-06T00:20:40.065845Z digest=sha256:0b287af2fa81eb0e06166eaa6314d132cf492fe022ddbe1f92f50a28b065f73f

Observation ab23ebee-b632-4e80-ae75-1775ba2bac1d · outbound

This paper cites StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimization.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents StepSearch: Igniting LLMs Search Ability via Step-Wise Proximal Policy Optimization

Reference 18

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source=pdf_text observed=2026-08-06T00:20:40.072107Z digest=sha256:59144b6eecfe96d5c89d0d7c466f00e11fae4f1f2e52920eabef0bb7e4e459af

Observation 878869e0-f040-4002-b8d7-acc39c797f6f · outbound

This paper cites arXiv:2603.22293.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents arXiv:2603.22293

Reference 19

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source=pdf_text observed=2026-08-06T00:20:40.074774Z digest=sha256:f7392084be2f9ed3a1476eb186d8c9f1e0828b11c2a396ffcaa3cce0a3ad7056

Observation 65f12af4-fb4b-44aa-99a9-56d885ef92ca · outbound

This paper cites Self-Distilled RLVR.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Self-Distilled RLVR

Reference 20

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source=pdf_text observed=2026-08-06T00:20:40.077361Z digest=sha256:8ce8c35f06198e2e02025a2e1e3c7bfeb9d71fc2b30e20e2c7fb67e8e438c565

Observation 3b71d3cc-506b-477f-93de-e8150b9ea7b5 · outbound

This paper cites arXiv:2511.12159.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents arXiv:2511.12159

Reference 22

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source=pdf_text observed=2026-08-06T00:20:40.082702Z digest=sha256:838ecdaf9f1da0b5cea312412abe244408bc5fbfd8c810834c76131a967348e6

Observation a1593114-c669-449b-91a4-18a2fd4df80c · outbound

This paper cites Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 23

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source=pdf_text observed=2026-08-06T00:20:40.085347Z digest=sha256:07ba7949d0d97cf9d08a220cbeecccfa2cb4316e036ce68a76da7127f4989c57

Observation 81ce34cf-33b8-49f6-aed1-454a3625f1cd · outbound

This paper cites Harry Potter and the Deathly Hallows.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Harry Potter and the Deathly Hallows

Reference 300

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verified fuzzy
raw_fallback, observed 2026-08-06T00:20:40.591602Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T00:20:40.088199Z digest=sha256:37eca1cbfa57f724931a1f1a3eb57356e8c0fc7a4c2052b5cb9ddeac31072ea1

Observation c98da8f0-efed-41f5-9f9e-3bdaf21b7132 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 2018

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source=pdf_text observed=2026-08-06T00:20:40.080060Z digest=sha256:5c6dbc8a08389bfd72c44506c45be7562b80e9367fcd2f5de5ac5497d02341ca

Observation 4b443a19-0b89-4cdd-a180-b99d8c545a0f · outbound

This paper cites What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents

Reference 2019

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:20:40.038407Z digest=sha256:3f3a9883d18d05970edfdb37ba527bed42e1c2f5c0d16f8daa1b264bc136893c

Observation 2cda83ce-8fc0-4024-a02d-80aa7b1babce · outbound

This paper cites In Webber, B.; Cohn, T.; He, Y.; and Liu, Y., eds.,Proceedings of the 2020 Confer- ence on Empirical Methods in Natural Language Processing (EMNLP), 6769–6781.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents In Webber, B.; Cohn, T.; He, Y.; and Liu, Y., eds.,Proceedings of the 2020 Confer- ence on Empirical Methods in Natural Language Processing (EMNLP), 6769–6781

Reference 2020

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verified fuzzy
raw_fallback, observed 2026-08-06T00:20:40.603849Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T00:20:40.035507Z digest=sha256:a6daf0790e6b850b3dd0ba5801a4bb1ba01fddbe6282724967f7f1fab01b1390

Observation 4d8b61c3-1c1a-4800-9d13-e32c346d9d39 · outbound

This paper cites MuSiQue: Multihop Questions via Single-hop Question Composition.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents MuSiQue: Multihop Questions via Single-hop Question Composition

Reference 2022

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:20:40.069413Z digest=sha256:bbf3b05518660c23a1fcf1581c629bc10b312389a2237c1b5ebfc0c292596528

Observation 1ae5e351-230b-43ae-9bc9-348a3582ed2c · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Measuring and Narrowing the Compositionality Gap in Language Models

Reference 2023

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source=pdf_text observed=2026-08-06T00:20:40.051262Z digest=sha256:94766b2fa1950d9b93c5444cfaeff93f986036385cc19f9c5c26fee8d30e9baa

Observation 43a1ed49-c941-46ee-bf07-32aa02d0b6f7 · outbound

This paper cites Group-in-Group Policy Optimization for LLM Agent Training.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Group-in-Group Policy Optimization for LLM Agent Training

Reference 2025

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:20:40.029217Z digest=sha256:b3ab3aad733658edb7a979d0fb5750a609c1b553f20771ebcf68ec821843915d

Observation f55ec6c8-b73d-4f66-842b-7cff11880a0d · outbound

This paper cites Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning.

EviSD: Evidence-Conditioned Self-Distillation for Search-Augmented Agents Beyond Trajectory-Level Attribution: Graph-Based Credit Assignment for Agentic Reinforcement Learning

Reference 2026

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verified exact
local_arxiv, observed 2026-08-06T00:20:40.569461Z

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

source=pdf_text observed=2026-08-06T00:20:40.022198Z digest=sha256:8ccf2ec72a6a6fad6d17473d08e47f2ab099e40449eb232fd9ae56575c57256c

Pith citing papers

No inbound Pith citation observations are available.