Paper Citation Record · LEDGER

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2506.11108.

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

pith.paper-citation-record.v1
2506.11108 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:52:37.467712Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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 exact0
verified fuzzy12
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 72d0b169-3be9-4ad3-b19a-a649f5e48bb2 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.384927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95fc398d-a297-4f1c-8d98-b458fc6fc4de · outbound

This paper cites Language models are few-shot learners.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Language models are few-shot learners

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.740477Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 83ae9183-4e70-4620-b61b-65f555a32da2 · outbound

This paper cites an unresolved cited work.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:52:37.730864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9e3cc82-2c77-42fe-9f70-a59af461c138 · outbound

This paper cites Proximal Policy Optimization Algorithms.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Proximal Policy Optimization Algorithms

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.397713Z

Source-reported events for the cited work

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Observation c5296904-1e35-4486-90f4-70d32b9ce972 · outbound

This paper cites an unresolved cited work.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:52:37.721317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e61d4da4-d49a-4d25-b718-a9518800205f · outbound

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

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Training language models to follow instructions with human feedback

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.405709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ddc4387c-1470-43ea-9c0d-159fe149b04a · outbound

This paper cites Gomez, Łukasz Kaiser, and Illia Polosukhin.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.711382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0e4178c0-d51f-44b3-9909-0b9cf4367ed0 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Fine-Tuning Language Models from Human Preferences

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.413252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 69c3fb62-ea1b-4370-9c14-13645bb1e41c · outbound

This paper cites Forbidding Edges between Points in the Plane to Disconnect the Triangulation Flip Graph.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Forbidding Edges between Points in the Plane to Disconnect the Triangulation Flip Graph

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4ea29d57-e741-4927-bbac-f4f04f0a78e3 · outbound

This paper cites A Self-Supervised Reinforcement Learning Approach for Fine-Tuning Large Language Models Using Cross-Attention Signals.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM A Self-Supervised Reinforcement Learning Approach for Fine-Tuning Large Language Models Using Cross-Attention Signals

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.420740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 846290f6-a6b0-4630-b414-6dc7278644c8 · outbound

This paper cites Of Spiky SVDs and Music Recommendation.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Of Spiky SVDs and Music Recommendation

Reference 11

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T05:52:37.512806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c2cb8527-6812-487d-9d03-8a76b2428d1d · outbound

This paper cites MultiWOZ—a Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM MultiWOZ—a Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.701855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4d91aee7-e62e-4922-b537-758cb1c5dc4e · outbound

This paper cites Revisiting Self-Training for Neural Sequence Production.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Revisiting Self-Training for Neural Sequence Production

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.692145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a603438-15e4-4886-953d-5163a5e466af · outbound

This paper cites MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM MSMatch: Semi-Supervised Multispectral Scene Classification with Few Labels

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T05:52:37.434235Z

Source-reported events for the cited work

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Observation 764905fd-a53d-4052-8763-0ddd164b93f6 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.682326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 022d703c-b974-4e7b-93cf-0b867d6ea5ec · outbound

This paper cites Self-Coherence Score: Learning to Verify Reasoning Paths in Large Language Models.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Self-Coherence Score: Learning to Verify Reasoning Paths in Large Language Models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.672657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8b29ce70-553b-44d5-95c6-95b31b4709a1 · outbound

This paper cites Towards Learning to Explain: An Attention-Based Self-supervised Approach for Improving Multi-turn Dialogue Mod- els.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Towards Learning to Explain: An Attention-Based Self-supervised Approach for Improving Multi-turn Dialogue Mod- els

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.662076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eede9a13-b25e-4d6c-a7af-2b0f3b5ededd · outbound

This paper cites Deep Reinforcement Learning for Dialogue Generation.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Deep Reinforcement Learning for Dialogue Generation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.651273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c4a4364f-c68c-4ec6-8331-d7f828067bec · outbound

This paper cites Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Serban, Michael Noseworthy, Laurent Charlin, Joelle Pineau

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.640452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d2a4a14f-8c88-460f-974c-d130dd9f710b · outbound

This paper cites Global Contextual Reinforcement Learning for Multi-Turn Dialogue.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Global Contextual Reinforcement Learning for Multi-Turn Dialogue

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.629095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e99d459-4187-4367-a9ff-e644468930e8 · outbound

This paper cites an unresolved cited work.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:52:37.618657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4ebcfa9-5b09-4cb7-a35d-de0961c06ae5 · outbound

This paper cites Self-Supervised Learning for Cross-Attention in Neural Text Generation.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Self-Supervised Learning for Cross-Attention in Neural Text Generation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.608483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb3fbd76-b702-40c7-a15d-10a9e7fe4afc · outbound

This paper cites an unresolved cited work.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-07T05:52:37.597791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a8349cd4-dc5c-4e84-8523-89a1cee13161 · outbound

This paper cites Ziegler, Ryan Lowe, Ilya Sutskever, and Paul F.

History-Aware Cross-Attention Reinforcement: Self-Supervised Multi Turn and Chain-of-Thought Fine-Tuning with vLLM Ziegler, Ryan Lowe, Ilya Sutskever, and Paul F

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:52:37.587437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.