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Paper Citation Record · LEDGER

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning

As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2607.15736.

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

pith.paper-citation-record.v1
2607.15736 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:30:30.736777Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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Outbound references

Observation 804d9cb0-e422-4b48-9a42-df52fb8bc6b0 · outbound

This paper cites On-policy distillation of language models: Learning from self-generated mistakes.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning On-policy distillation of language models: Learning from self-generated mistakes

Reference 1

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source=pdf_text observed=2026-08-01T22:30:26.312230Z digest=sha256:a106cbe817b0f7569171dac04dd16b3fe93da7dea3a4278aa25e0feaeebf9821

Observation 4ca6bead-6994-420f-a141-59d3a0c82426 · outbound

This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Reference 2

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source=pdf_text observed=2026-08-01T22:30:26.382580Z digest=sha256:987ef1d13ddacc73b9384ab3b2bd3cc90c916143d49faef1e1b6244f20afa76a

Observation 71580838-4a00-4043-b714-62b35e844fac · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Evaluating Large Language Models Trained on Code

Reference 3

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source=pdf_text observed=2026-08-01T22:30:26.437579Z digest=sha256:d8a4632116ca4d6b97f97f71940bbf67552da95946fca9716c13c17856e92fda

Observation b2d756ed-7aef-46f3-a18d-08c8796c2180 · outbound

This paper cites Over-reasoning and redundant calculation of large language models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Over-reasoning and redundant calculation of large language models

Reference 4

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source=pdf_text observed=2026-08-01T22:30:26.574381Z digest=sha256:24c747f60dfe1d3632cb0ebeecd103a532eab631299218604d9549224df54821

Observation 4aec21af-58bb-4c93-8c00-71d71bec22cb · outbound

This paper cites Ctrlcot: Dual-granularity chain-of-thought compression for controllable reasoning.arXiv preprint arXiv:2601.20467, 2026.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Ctrlcot: Dual-granularity chain-of-thought compression for controllable reasoning.arXiv preprint arXiv:2601.20467, 2026

Reference 5

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source=pdf_text observed=2026-08-01T22:30:26.709576Z digest=sha256:22604eae9d99ccabcd174b3717d482d21626a18919d5a64e86dec6677f369c28

Observation 23771348-14da-43d3-85e7-1bf00c307d4e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 6

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source=pdf_text observed=2026-08-01T22:30:26.806144Z digest=sha256:bfb90a202f8cefcedc4aacc286dd27d2b163d45e03309edf45676397aa74c7ee

Observation cc4ec9f7-12a1-45a4-9c29-d8702dac0d2d · outbound

This paper cites FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning FADE: Mitigating Hallucinations by Reducing Language-Prior Dominance in Large Vision-Language Models

Reference 7

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source=pdf_text observed=2026-08-01T22:30:26.949438Z digest=sha256:c8498fcdcadb9f00fba65d45e423a970b92c67a41641a3848ddc9d2fe6375a38

Observation 0584c0fa-fd79-4637-b482-b9222a1d19ad · outbound

This paper cites Lora: Low-rank adaptation of large language models.Iclr, 1(2):3, 2022.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Lora: Low-rank adaptation of large language models.Iclr, 1(2):3, 2022

Reference 8

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source=pdf_text observed=2026-08-01T22:30:27.059754Z digest=sha256:3350f252058e29fe0f8dcd240fdfc775fee574e68ff44b9305f80122bd557a37

Observation 71436f62-523a-4f94-b8c9-41869fc84566 · outbound

This paper cites CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning CFMS: A Coarse-to-Fine Multimodal Synthesis Framework for Enhanced Tabular Reasoning

Reference 9

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source=pdf_text observed=2026-08-01T22:30:27.185941Z digest=sha256:a1c0e2940ea5dd85645dc1f1f58a9606f80d6c70e6057b3bb17782a2800faa9f

Observation ce4b9a58-09c5-4fde-a45f-392571590ab6 · outbound

This paper cites Stepwise penalization for length-efficient chain-of-thought reasoning.arXiv preprint arXiv:2603.00296, 2026.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Stepwise penalization for length-efficient chain-of-thought reasoning.arXiv preprint arXiv:2603.00296, 2026

Reference 10

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source=pdf_text observed=2026-08-01T22:30:27.342651Z digest=sha256:cedeb1b9da36c3355bed3e1ba0a385c8426eeeed5edeb3b5b63858c198d0a11b

Observation 5b7fbd9e-57fc-47ec-bd72-7c61dbc45b65 · outbound

This paper cites Leash: Adaptive length penalty and reward shaping for efficient large reasoning model.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Leash: Adaptive length penalty and reward shaping for efficient large reasoning model

Reference 11

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source=pdf_text observed=2026-08-01T22:30:27.465715Z digest=sha256:3d1a6f42568691f0c8475e62be2057be48e5fddf22dd57f4739685064daf8b3a

Observation 5ba74e4f-fc37-4b55-8f29-fcc8a19eb7ab · outbound

This paper cites Filter, Then Reweight: Rethinking Optimization Granularity in On-Policy Distillation.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Filter, Then Reweight: Rethinking Optimization Granularity in On-Policy Distillation

Reference 12

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source=pdf_text observed=2026-08-01T22:30:27.604900Z digest=sha256:d764129780536c3646a4c2671a057e1f3a7aff2653531dc70f4e3c9f985cd405

Observation 9ee0426e-f059-4a07-9eb6-34c0452fb5c5 · outbound

This paper cites Making slow thinking faster: Compressing llm chain-of-thought via step entropy.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Making slow thinking faster: Compressing llm chain-of-thought via step entropy

Reference 13

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source=pdf_text observed=2026-08-01T22:30:27.734791Z digest=sha256:4d06b67038e2329c106bce6f55e70d2a178a2832d988025a69debab233a905a9

Observation a7e33486-b871-43fb-80cd-52bcf714811c · outbound

This paper cites Cot-valve: Length- compressible chain-of-thought tuning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Cot-valve: Length- compressible chain-of-thought tuning

Reference 14

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source=pdf_text observed=2026-08-01T22:30:27.867246Z digest=sha256:0f4cf0bc5a19b78871fcfb1fc2671c8bbd3033ee043d9e1850fbbc56e9ffb145

Observation 0a0d4f9a-1cc5-4e56-9b8c-dcc1d45a5c81 · outbound

This paper cites Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt

Reference 15

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source=pdf_text observed=2026-08-01T22:30:27.977843Z digest=sha256:f4c8cf8ba21e2ac2c4b78f1cf5cf912ebde97596785cb233814b53926beb9bce

Observation afa4a953-3909-43b0-aa0b-fafb28be5eb1 · outbound

This paper cites The Benefits of a Concise Chain of Thought on Problem-Solving in Large Language Models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning The Benefits of a Concise Chain of Thought on Problem-Solving in Large Language Models

Reference 16

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source=pdf_text observed=2026-08-01T22:30:28.075136Z digest=sha256:4e066cdd04eb924b9fe893ba0eef340ade3199c217c3e9225c6aa31eaf2a456a

Observation fe6823c0-5e7f-4cbe-82eb-c29ce392c66e · outbound

This paper cites CRISP: Compressed Reasoning via Iterative Self-Policy Distillation.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning CRISP: Compressed Reasoning via Iterative Self-Policy Distillation

Reference 17

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source=pdf_text observed=2026-08-01T22:30:28.143346Z digest=sha256:31baa40cf237362c9fcaf616fa0196f24df588120c6dd5f1f96cb99b7cf1ddbc

Observation 5b00ecb9-7a1c-44af-8f27-118e5554b71f · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 18

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source=pdf_text observed=2026-08-01T22:30:28.188121Z digest=sha256:a0d39cc72ed2066dceb0401666e1f7aa971d48987fb36e12e5e5f7a12eb25abd

Observation 270477ff-04a5-465b-a9fb-d2544c49303c · outbound

This paper cites Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Mitigating Hallucinations via Inter-Layer Consistency Aggregation in Large Vision-Language Models

Reference 19

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source=pdf_text observed=2026-08-01T22:30:28.272756Z digest=sha256:1d226bbb8b1fcdb4e059dd839e38a2472937509429d5feee446d6555ea911a90

Observation 38483ab5-3502-41d5-8e6b-e19e2bfebca4 · outbound

This paper cites SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering

Reference 20

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source=pdf_text observed=2026-08-01T22:30:28.401425Z digest=sha256:c55bd423213ca58a8793acb9489750c1f1a21de5f246f97f5543a8a175dd197e

Observation 82c46945-f09b-4956-9e47-cd4997d2cdd5 · outbound

This paper cites Mitigating overthinking in large reasoning models via difficulty-aware reinforcement learning.arXiv preprint arXiv:2601.21418, 2026.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Mitigating overthinking in large reasoning models via difficulty-aware reinforcement learning.arXiv preprint arXiv:2601.21418, 2026

Reference 21

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source=pdf_text observed=2026-08-01T22:30:28.521507Z digest=sha256:bbf797322718d9b68ccc036085d794e1dc351e7cc70107fd5b9c2ee513209887

Observation 78dd7ee1-1831-4003-8622-8a91d09a4dcc · outbound

This paper cites Pointrft: Explicit reinforcement fine-tuning for point cloud few-shot learning.arXiv preprint arXiv:2603.23957, 2026.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Pointrft: Explicit reinforcement fine-tuning for point cloud few-shot learning.arXiv preprint arXiv:2603.23957, 2026

Reference 22

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source=pdf_text observed=2026-08-01T22:30:28.646872Z digest=sha256:8acc69a1a318a6ba364a6a5ee54f5a80416c503526e3b5d0f857d7aa06809e33

Observation 87e7945c-1293-4074-a41a-cd85eacc6e7c · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Chain-of-thought prompting elicits reasoning in large language models.Advances in neural information processing systems, 35:24824–24837, 2022

Reference 23

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source=pdf_text observed=2026-08-01T22:30:28.751256Z digest=sha256:45e709cf399bf54c031afeb84c41a87408b956addbe5f01f6fe164d8fce33942

Observation 2cfc9306-1f12-4bd2-8e43-202a8f59d53e · outbound

This paper cites Stop spinning wheels: Mitigating llm overthinking via mining patterns for early reasoning exit.arXiv preprint arXiv:2508.17627, 2025.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Stop spinning wheels: Mitigating llm overthinking via mining patterns for early reasoning exit.arXiv preprint arXiv:2508.17627, 2025

Reference 24

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source=pdf_text observed=2026-08-01T22:30:28.856639Z digest=sha256:d0d2685212c1bf3310a84ca5246effd70ed599cda1cce96a34e83022e6aa111d

Observation 8d425e2d-bf39-4158-b6a5-3991ea88868d · outbound

This paper cites Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

Reference 25

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source=pdf_text observed=2026-08-01T22:30:29.031776Z digest=sha256:c9e0886ade89dcb950a95cbfa5a428a07398ef0cc53ee1eaa90c4130783055a7

Observation 3d6ea4e8-f89d-47ae-8438-c12168969145 · outbound

This paper cites Tokenskip: Controllable chain-of- thought compression in llms.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Tokenskip: Controllable chain-of- thought compression in llms

Reference 26

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source=pdf_text observed=2026-08-01T22:30:29.190178Z digest=sha256:6ca77bb08b0aa2320614a091acd2f08357b4b0b050ca64b8a2d989ac6626a29d

Observation 5c24fd4d-33e7-4894-9235-6b49b96cef7d · outbound

This paper cites TIP: Token Importance in On-Policy Distillation.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning TIP: Token Importance in On-Policy Distillation

Reference 27

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source=pdf_text observed=2026-08-01T22:30:29.298845Z digest=sha256:c2de4cf7e9d9614ec02b954e8c2081e6b8cc5deeccb9a23105b5ed272c6a34dc

Observation 724d3a4e-c076-4d70-ac1f-017cd7a5a2e8 · outbound

This paper cites Qwen3 Technical Report.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Qwen3 Technical Report

Reference 28

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source=pdf_text observed=2026-08-01T22:30:29.435203Z digest=sha256:96cf1d6f972a40a38726313d82bf105d66716cd0fa06c949e5f2469ddeb4b9b3

Observation 42a0bf48-4449-4bce-af68-bd9b3541a50f · outbound

This paper cites Dynamic early exit in reasoning models.arXiv preprint arXiv:2504.15895, 2025.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Dynamic early exit in reasoning models.arXiv preprint arXiv:2504.15895, 2025

Reference 29

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source=pdf_text observed=2026-08-01T22:30:29.581049Z digest=sha256:4dab65f4daddf5222ee6931bd56ad1219d41980ea66b44b9102422d481dff5b8

Observation df229ce0-1db5-4f8c-80cc-8ecb0b81639e · outbound

This paper cites Dapo: An open-source llm reinforcement learning system at scale.Advances in Neural Information Processing Systems, 38:113222–113244, 2026.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Dapo: An open-source llm reinforcement learning system at scale.Advances in Neural Information Processing Systems, 38:113222–113244, 2026

Reference 30

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source=pdf_text observed=2026-08-01T22:30:29.705899Z digest=sha256:fc2d8fc9b9a076a0471558773b7a5cc7607bb0a554ae279e1b56964c6ef84e69

Observation 05a0f91a-5b99-4951-8846-aec3d412fd80 · outbound

This paper cites Not All Errors Are Created Equal: ASCoT Addresses Late-Stage Fragility in Efficient LLM Reasoning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Not All Errors Are Created Equal: ASCoT Addresses Late-Stage Fragility in Efficient LLM Reasoning

Reference 31

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source=pdf_text observed=2026-08-01T22:30:29.855076Z digest=sha256:647dfd980f3b3ed87ba8297ce98feb2d043e4fef782f2b8b57174bd04120e809

Observation 5d6f8778-4ca5-491c-af35-36fc05297cde · outbound

This paper cites Not all queries need deep thought: Coficot for adaptive coarse-to-fine stateful refinement.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Not all queries need deep thought: Coficot for adaptive coarse-to-fine stateful refinement

Reference 32

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source=pdf_text observed=2026-08-01T22:30:29.983687Z digest=sha256:81175264d3eeb83ebe91534c88b1511f0de9304e1873c12137ff2e918180506f

Observation 963e6cda-bb0b-4ced-a1b5-ba1ac8760988 · outbound

This paper cites Pointcot: A multi-modal benchmark for explicit 3d geometric reasoning.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Pointcot: A multi-modal benchmark for explicit 3d geometric reasoning

Reference 33

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source=pdf_text observed=2026-08-01T22:30:30.130283Z digest=sha256:3f71b80b2c4d6fd3ce749b50cec4b330a17f7796fd05346412a7d047b26087bd

Observation c450edfb-9a75-4e2c-aadd-849da054a64c · outbound

This paper cites Chain-of- thought compression should not be blind: V-skip for efficient multimodal reasoning via dual-path anchoring.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Chain-of- thought compression should not be blind: V-skip for efficient multimodal reasoning via dual-path anchoring

Reference 34

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source=pdf_text observed=2026-08-01T22:30:30.246127Z digest=sha256:ef49d463b78b2090cdf06e14540ee71b3c94ebf308cb79ddb0621cf174616753

Observation aa0c6422-aac5-40c6-ad1c-39a49fad9520 · outbound

This paper cites find the time 1000 days later.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning find the time 1000 days later

Reference 35

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source=pdf_text observed=2026-08-01T22:30:30.383699Z digest=sha256:714645b20e1b9592fcfa0e441393e045ffbc67e680fae025e6498dbf72c383a2

Observation 55b36b39-b8ab-4adb-aa77-48b40343be77 · outbound

This paper cites OPSDL: On-Policy Self-Distillation for Long-Context Language Models.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning OPSDL: On-Policy Self-Distillation for Long-Context Language Models

Reference 36

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source=pdf_text observed=2026-08-01T22:30:30.506956Z digest=sha256:fc9806531f99d893d50ebb1bcf26367455e6cdb2b7012fa2ad528738b9ca47cc

Observation 1ce0a45e-fefc-4f5a-88a4-1f59748e649e · outbound

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

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 37

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source=pdf_text observed=2026-08-01T22:30:30.618642Z digest=sha256:fb0c0c88c42c3fa603199e1546f01d06b944d54345ca94abb1b9a83f815f3ee3

Observation aae79c50-4483-4cf4-ba8b-7467a79da262 · outbound

This paper cites ROSD: Reflective On-Policy Self-Distillation for Language Model Reasoning across Domains.

Better Starts, Better Ends: Bootstrapped Iterative Self-Reasoning Distillation for Compressed Reasoning ROSD: Reflective On-Policy Self-Distillation for Language Model Reasoning across Domains

Reference 38

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no resolver link, observed 2026-08-01T22:30:30.736777Z

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source=pdf_text observed=2026-08-01T22:30:30.736777Z digest=sha256:065a1772eee338e43d3f1297c2052a522c46f55d72499ee591fdeab27e823394

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