Paper Citation Record · LEDGER

Rho-1: Not All Tokens Are What You Need

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2404.07965.

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

pith.paper-citation-record.v1
2404.07965 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:01:03.397522Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4145d778-536d-425b-96ee-0ee01afc7c07 · inbound

DataComp-LM: In search of the next generation of training sets for language models cites this paper.

DataComp-LM: In search of the next generation of training sets for language models Rho-1: Not All Tokens Are What You Need

Reference 108

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:58:17.066499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4b075053-92a5-4a37-8f89-3f69aefd8a91 · inbound

Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs cites this paper.

Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs Rho-1: Not All Tokens Are What You Need

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T23:58:29.135044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f0233435-99e1-408e-a4d0-e29fa6e04b4d · inbound

One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs cites this paper.

One Example Shown, Many Concepts Known! Counterexample-Driven Conceptual Reasoning in Mathematical LLMs Rho-1: Not All Tokens Are What You Need

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T11:01:03.397522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95ee720f-f476-4f9e-b569-0f3e85e7c30c · inbound

Learning to Reason at the Frontier of Learnability cites this paper.

Learning to Reason at the Frontier of Learnability Rho-1: Not All Tokens Are What You Need

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:42:26.218182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e59e25b1-d230-4505-b4dd-5b381d0f9aad · inbound

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining cites this paper.

ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining Rho-1: Not All Tokens Are What You Need

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T14:09:47.959331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4088bc24-c3d9-4787-8e90-48c51ab95d93 · inbound

Probability-Consistent Preference Optimization for Enhanced LLM Reasoning cites this paper.

Probability-Consistent Preference Optimization for Enhanced LLM Reasoning Rho-1: Not All Tokens Are What You Need

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:48:50.753591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 877563c6-5bb8-43ae-b7ed-0d986c0eaca0 · inbound

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning cites this paper.

Not Every Token Needs Forgetting: Selective Unlearning to Limit Change in Utility in Large Language Model Unlearning Rho-1: Not All Tokens Are What You Need

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:03:34.041761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91758f7d-7bab-446c-a2b6-6158350f00ec · inbound

Demystifying Reasoning Dynamics with Mutual Information: Thinking Tokens are Information Peaks in LLM Reasoning cites this paper.

Demystifying Reasoning Dynamics with Mutual Information: Thinking Tokens are Information Peaks in LLM Reasoning Rho-1: Not All Tokens Are What You Need

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T11:19:46.493246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 403d8a32-ff29-4590-a22e-5aee1a14e224 · inbound

A Survey on Large Language Models for Mathematical Reasoning cites this paper.

A Survey on Large Language Models for Mathematical Reasoning Rho-1: Not All Tokens Are What You Need

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T05:14:47.351148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7bba15c1-ce11-4a95-b04b-30fe549d7e98 · inbound

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law cites this paper.

Capability Salience Vector: Fine-grained Alignment of Loss and Capabilities for Downstream Task Scaling Law Rho-1: Not All Tokens Are What You Need

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:00.976666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97c019cf-d445-45f6-b6bb-9652cfd16282 · inbound

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models cites this paper.

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models Rho-1: Not All Tokens Are What You Need

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:15:34.227513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be8874e2-b0a5-42da-9f9e-cffd68cd07d8 · inbound

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs cites this paper.

RefineX: Learning to Refine Pre-training Data at Scale from Expert-Guided Programs Rho-1: Not All Tokens Are What You Need

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:21:51.821393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06679556-0779-4f82-915d-41f4319bf107 · inbound

Read Quietly, Think Aloud: Decoupling Comprehension and Reasoning in LLMs cites this paper.

Read Quietly, Think Aloud: Decoupling Comprehension and Reasoning in LLMs Rho-1: Not All Tokens Are What You Need

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:18:15.688795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f567fc3-240d-42c3-9de7-06984d22f8d7 · inbound

Not All Preferences are What You Need for Post-Training: Selective Alignment Strategy for Preference Optimization cites this paper.

Not All Preferences are What You Need for Post-Training: Selective Alignment Strategy for Preference Optimization Rho-1: Not All Tokens Are What You Need

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:38:10.027182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5c318d5-05a2-429f-a5d3-c4ee9a981f3b · inbound

Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.

Language Models Improve When Pretraining Data Matches Target Tasks Rho-1: Not All Tokens Are What You Need

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T16:53:11.243914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbe78087-5486-4b00-9712-d0ca4cdbea02 · inbound

ReGATE: Learning Faster and Better with Fewer Tokens in MLLMs cites this paper.

ReGATE: Learning Faster and Better with Fewer Tokens in MLLMs Rho-1: Not All Tokens Are What You Need

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:22:01.226237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e4daea9-925e-4962-ac34-7143ff219f13 · inbound

Hardness-Aware Dynamic Curriculum Learning for Robust Multimodal Emotion Recognition with Missing Modalities cites this paper.

Hardness-Aware Dynamic Curriculum Learning for Robust Multimodal Emotion Recognition with Missing Modalities Rho-1: Not All Tokens Are What You Need

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T22:36:43.649644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03963849-4861-4932-88bd-632a4a9077c3 · inbound

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models cites this paper.

VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models Rho-1: Not All Tokens Are What You Need

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T22:41:54.056264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 74600b74-d345-4bf1-970a-03f436b15788 · inbound

Masked Diffusion Language Models with Frequency-Informed Training cites this paper.

Masked Diffusion Language Models with Frequency-Informed Training Rho-1: Not All Tokens Are What You Need

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T05:46:28.436696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ede234-2401-4b0b-9e61-1067258d1c64 · inbound

RadarPLM: Adapting Pre-trained Language Models for Marine Radar Target Detection by Selective Fine-tuning cites this paper.

RadarPLM: Adapting Pre-trained Language Models for Marine Radar Target Detection by Selective Fine-tuning Rho-1: Not All Tokens Are What You Need

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:01:34.637767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4e99f72d-dced-45aa-bcd4-20c497716d84 · inbound

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models cites this paper.

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models Rho-1: Not All Tokens Are What You Need

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T14:51:30.219045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c01e431c-1ded-4800-baaa-2d5664e4efa6 · inbound

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models cites this paper.

GIFT: Guided Importance-Aware Fine-Tuning for Diffusion Language Models Rho-1: Not All Tokens Are What You Need

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T14:51:29.829990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1b65ce9e-cae7-45ab-a332-37dfa695f3b2 · inbound

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning? cites this paper.

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning? Rho-1: Not All Tokens Are What You Need

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:01:34.009777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 73e7b422-da06-4a95-a442-7bb59e8b46fd · inbound

Training-Trajectory-Aware Token Selection cites this paper.

Training-Trajectory-Aware Token Selection Rho-1: Not All Tokens Are What You Need

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-22T11:41:29.587727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2d28eb3c-3d01-473e-b40d-45259048bf83 · inbound

Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation cites this paper.

Don't Ignore the Tail: Decoupling top-K Probabilities for Efficient Language Model Distillation Rho-1: Not All Tokens Are What You Need

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T20:10:17.997841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 82a5af6b-56d8-4f88-a079-ff1dbdc67dd8 · inbound

GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning cites this paper.

GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning Rho-1: Not All Tokens Are What You Need

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T21:05:25.711054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 241424ad-a14b-4432-8710-db8a3876f968 · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis Rho-1: Not All Tokens Are What You Need

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T18:10:13.256835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d7ca72a4-9fa5-4005-94ab-5957cc4f4893 · inbound

Understanding LoRA as Knowledge Memory: An Empirical Analysis cites this paper.

Understanding LoRA as Knowledge Memory: An Empirical Analysis Rho-1: Not All Tokens Are What You Need

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T19:49:45.151728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0494852a-730f-4f7d-bb1a-ea94a7b6420f · inbound

SPREG: Structured Plan Repair with Entropy-Guided Test-Time Intervention for Large Language Model Reasoning cites this paper.

SPREG: Structured Plan Repair with Entropy-Guided Test-Time Intervention for Large Language Model Reasoning Rho-1: Not All Tokens Are What You Need

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:02.797848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e0d41d1c-65d1-4bad-aa7c-9277cac97cd9 · inbound

Selective Contrastive Learning For Gloss Free Sign Language Translation cites this paper.

Selective Contrastive Learning For Gloss Free Sign Language Translation Rho-1: Not All Tokens Are What You Need

Reference 7

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:31:10.178344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eb1877d1-0aec-459b-80dd-3a71fab9ea28 · inbound

CODEBLOCK: Learning to Supervise Code at the Right Granularity cites this paper.

CODEBLOCK: Learning to Supervise Code at the Right Granularity Rho-1: Not All Tokens Are What You Need

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T08:17:45.472573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eef586f3-1521-4934-b262-7cb4f560ebc5 · inbound

DomainPilot: Domain-Level Loss-Guided Two-Stage Data Mixture Optimization for Efficient Language Model Fine-Tuning cites this paper.

DomainPilot: Domain-Level Loss-Guided Two-Stage Data Mixture Optimization for Efficient Language Model Fine-Tuning Rho-1: Not All Tokens Are What You Need

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T06:19:32.644746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0de724b4-9a24-409a-8695-89c258a522de · inbound

Bridging Compute- and Data-Optimal Pretraining cites this paper.

Bridging Compute- and Data-Optimal Pretraining Rho-1: Not All Tokens Are What You Need

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-01T03:02:03.996810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.