Paper Citation Record · LEDGER

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2506.09408.

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

pith.paper-citation-record.v1
2506.09408 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:54:44.781763Z

measured 14 of 14 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.

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

14 of 14 outbound references displayed

verified exact0
verified fuzzy1
unresolved13
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 963e6880-4064-4d65-aeb5-13172749dc7e · outbound

This paper cites Language Models are Few-Shot Learners.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Language Models are Few-Shot Learners

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:43.854018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8392326-2480-469f-b75e-114cffc867bd · outbound

This paper cites Reasoning robustness of LLM s to adversarial typographical errors.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Reasoning robustness of LLM s to adversarial typographical errors

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:43.881021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b477e426-f676-462e-90c4-979f94dd01a5 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Measuring Massive Multitask Language Understanding

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:43.932206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ed9aae-b250-459f-ac00-09e5d4985201 · outbound

This paper cites A Study on Large Language Models' Limitations in Multiple-Choice Question Answering.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models A Study on Large Language Models' Limitations in Multiple-Choice Question Answering

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:43.993794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f230ba5-76ef-4560-b81c-4f34051830a7 · outbound

This paper cites PRD etect: Perturbation-robust LLM -generated text detection based on syntax tree.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models PRD etect: Perturbation-robust LLM -generated text detection based on syntax tree

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:54:45.071476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8ac2acf7-c037-4dfa-a342-f30fc517e4ae · outbound

This paper cites GPT-4 Technical Report.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models GPT-4 Technical Report

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.148928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3e6299b-8c9c-4ca4-9b08-7e3bcb022348 · outbound

This paper cites Leveraging Large Language Models for Multiple Choice Question Answering.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Leveraging Large Language Models for Multiple Choice Question Answering

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.226947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f984af19-556f-4736-8cb9-4716fcd9b931 · outbound

This paper cites Large Language Models Can Be Easily Distracted by Irrelevant Context.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Large Language Models Can Be Easily Distracted by Irrelevant Context

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.293782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bc30309-c5ea-4f5c-86b6-f11d5616bc7d · outbound

This paper cites C ommonsense QA : A question answering challenge targeting commonsense knowledge.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models C ommonsense QA : A question answering challenge targeting commonsense knowledge

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.369906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e0642ca-d500-4b0a-b746-7a76ee8ebef1 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.455303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc8c4f00-7eb6-410a-8d51-130ba3097448 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.534424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df4c8b15-2066-4e1c-85e2-2c1d70781e79 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.606792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bdabd75-5050-4a3a-9d28-f3a3f996cbd8 · outbound

This paper cites mT5: A massively multilingual pre-trained text-to-text transformer.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models mT5: A massively multilingual pre-trained text-to-text transformer

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.696499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e58304cb-0941-4e1e-ab00-4e97ee0f4dfe · outbound

This paper cites Large Language Models Are Not Robust Multiple Choice Selectors.

Token Constraint Decoding Improves Robustness on Question Answering for Large Language Models Large Language Models Are Not Robust Multiple Choice Selectors

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T04:54:44.781763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.