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Paper Citation Record · LEDGER

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation

As of 9 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 1 inbound Pith citation observation for arXiv:2502.05911.

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

pith.paper-citation-record.v1
2502.05911 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:31:59.951364Z

measured 60 of 60 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T01:23:01.921132Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T01:25:34.979210Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact4
  • verified fuzzy2
  • unresolved53
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 31cd75f1-2fa6-4cda-93b0-b13659aa9c99 · outbound

This paper cites RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-08T17:32:00.378572Z

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=arxiv_source observed=2026-08-08T17:31:59.765632Z digest=sha256:d2406a798353e6d380e0ee112e73011e7d93de1bd6440729e0d3d69284724f2f

Observation b4b5c76b-2b33-428f-baf1-ef36367a6c38 · outbound

This paper cites Efficient Model-agnostic Alignment via Bayesian Persuasion.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Efficient Model-agnostic Alignment via Bayesian Persuasion

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.769377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.769377Z digest=sha256:b53b153a1cd2dc871bb3b283091e7156ec9c597d494a1f31e0b7832649775197

Observation 97cbe8de-681f-4aee-8d13-936e02b17731 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.508773Z

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=arxiv_source observed=2026-08-08T17:31:59.772795Z digest=sha256:99eb742810a61ee4498b3e2031baf594fe1f83fe191f5cb7ba0c813e824da132

Observation 18e2ba56-6341-44c8-b3d0-589e66b514d9 · outbound

This paper cites Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions

Reference 5

Resolution
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no resolver link, observed 2026-08-08T17:31:59.775874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.775874Z digest=sha256:a46da9fbbbd402225b1665dd50644f0cf1848b73eb0e7f7908ad3de898981c7b

Observation d4ac8346-95d8-49b3-be49-5d588b7dcc2e · outbound

This paper cites Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Teaching Large Language Models to Express Knowledge Boundary from Their Own Signals

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.779480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.779480Z digest=sha256:01c304429110f2d11006ede17a0774b36173aee493aae3babf7238771d4c5ca4

Observation a3359a1b-a55b-4c0e-9335-cf2814405e51 · outbound

This paper cites Can AI Assistants Know What They Don't Know?.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Can AI Assistants Know What They Don't Know?

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.783337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.783337Z digest=sha256:dbf9a70176a121435a8dce983c5fb96865a08866738e695837fc70fe82234cab

Observation ac8b7d7f-9149-49d4-9e40-d617761dbb7f · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.786697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.786697Z digest=sha256:37b7bfc5c22bc525fa4397630fe0931ee90916c47483d963acba6184f9269ece

Observation 7c26d678-0727-4566-88da-af77e191c3f6 · outbound

This paper cites Knowledge Neurons in Pretrained Transformers.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Knowledge Neurons in Pretrained Transformers

Reference 9

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no resolver link, observed 2026-08-08T17:31:59.789363Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.789363Z digest=sha256:60f9909d1a13acbff7b07e0cc4588f7c84138687b88e8ba7fcc567b396d53bee

Observation 3420928a-3a50-460c-b3a7-1425a68ea300 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.792195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.792195Z digest=sha256:6f3597239a2c0fc54356bf6f6f9fcf2456ea927fdc2b24a268952eacadfaafca

Observation e144b74d-ab38-48a2-b0b8-32305bcabc2c · outbound

This paper cites The Llama 3 Herd of Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation The Llama 3 Herd of Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.794895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.794895Z digest=sha256:41d6ba6354f64087e51e95072e55db62e27dad2c031c5e783cfd64c61595527f

Observation d1b452a8-a336-425d-a42a-a9cbfff375d0 · outbound

This paper cites Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Don't Hallucinate, Abstain: Identifying LLM Knowledge Gaps via Multi-LLM Collaboration

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.798068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.798068Z digest=sha256:cab5203ae219fe297be73a8bce73758582a50a08bfe75fc778d2a915b2e2b6de

Observation 56032f7f-3a9f-4bf5-8f60-5a264f06f9f6 · outbound

This paper cites Successor Heads: Recurring, Interpretable Attention Heads In The Wild.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Successor Heads: Recurring, Interpretable Attention Heads In The Wild

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.801158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.801158Z digest=sha256:2ab6d435604a43a3b76c6d906d008b6cca90943634c6e99c73373d74da7510fc

Observation 8282045c-f268-41fc-8588-fc6203cc46c3 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Measuring Massive Multitask Language Understanding

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.804096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.804096Z digest=sha256:898a0a3c8e297adb58f8a7efaaf2ccbb4bed2307c23b2374b57ed30abeb8ffc6

Observation 1a7a9c2d-3f2f-4731-af89-5c472a7fa147 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation LoRA: Low-Rank Adaptation of Large Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.807595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.807595Z digest=sha256:b4d6eac0d2400db17b2cee7a8c952a99a34bd6fe73558c709de3d8ab6590537c

Observation abf18524-daa3-4e47-a935-8b6e08c0640e · outbound

This paper cites Lora: Low-rank adaptation of large language models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Lora: Low-rank adaptation of large language models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.810829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.810829Z digest=sha256:a2bbde851136f4db1eea25dcb375d42e24c577d621cf4a76f481b5a18a38092a

Observation a8f0cb3b-5383-4bae-a944-53268445c686 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.813879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.813879Z digest=sha256:7fd9e30c03859d73686d26ffc23c5bf7728dab77094fb2e679e360f14a8f583c

Observation 637c8f11-9eae-419c-80e1-cf83d3a797a0 · outbound

This paper cites TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems

Reference 18

Resolution
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no resolver link, observed 2026-08-08T17:31:59.817364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.817364Z digest=sha256:f6bcb9fbe0ea1078884c3b269693d3562a4718a9d1173b5479cd7c2cefa73309

Observation fd7b17a7-b4e3-43e7-9c07-18ca3bd834b9 · outbound

This paper cites HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.820951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.820951Z digest=sha256:d8ac785f1facb4fd9b977b6c2f8683c8581cd69466b2b6933242d8816c278c18

Observation 4fea0eba-5208-4f40-bbe4-ade36c48fcad · outbound

This paper cites Johnson and Joram Lindenstrauss.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Johnson and Joram Lindenstrauss

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.823920Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.823920Z digest=sha256:2d770ec517ccb1ea49299114f5d4b146af7fa25b9341009fb83bcc6177135be2

Observation 7886acf6-e0f5-4cd5-a930-50db5c6a6460 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.827763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.827763Z digest=sha256:127c44f6ee6e2c5a34d161560a92944093410925c20a35716afc151ff39f8be2

Observation e847c900-f1ff-4b67-adb6-c42e79d94777 · outbound

This paper cites Unfamiliar Finetuning Examples Control How Language Models Hallucinate.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unfamiliar Finetuning Examples Control How Language Models Hallucinate

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.831137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.831137Z digest=sha256:2437e3c8eeb5033b6e1206c514d208f94ba19f7e42b2027ce34f084b79def2b0

Observation 2d274182-0347-4f98-a148-6fc5013bfcfb · outbound

This paper cites Scaling Laws for Neural Language Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Scaling Laws for Neural Language Models

Reference 23

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unresolved
no resolver link, observed 2026-08-08T17:31:59.834122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.834122Z digest=sha256:b51d62802d70dad3e7f844224fe52018f0ef3061ae9c8075b0c727ae2497a96f

Observation a48ee927-a83c-4218-8823-ba6bcaf698fb · outbound

This paper cites GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training

Reference 25

Resolution
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no resolver link, observed 2026-08-08T17:31:59.840500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.840500Z digest=sha256:0490c40dc8326b4d8b5af7865f43d654b5e147640ecd19e005844572dfb63cfc

Observation 74d034ec-774d-4d25-876f-f0999b45b9ea · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 26

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no resolver link, observed 2026-08-08T17:31:59.842715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.842715Z digest=sha256:ed7ad9aef475bf97b374f371cc3ba3d00faab3b2ed74aaf05daf698933be11d8

Observation 4f69519e-fed4-4bc7-b23a-0895dcdfcb86 · outbound

This paper cites A Survey on the Honesty of Large Language Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation A Survey on the Honesty of Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.844845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.844845Z digest=sha256:d26fe06010e2c95ed0a9c254958ccf91a4d3a2a0c783415112aecb9cb242be87

Observation 0ef876ad-e0c4-4a39-a5bd-2aebf392653c · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.482230Z

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=arxiv_source observed=2026-08-08T17:31:59.847112Z digest=sha256:28cdec6e8f9529a4d495687962410292be1d6006ca7c512b778946192c81cac5

Observation d0e44cc3-ed0f-4761-8386-0274115767e1 · outbound

This paper cites Kuaiji: the First Chinese Accounting Large Language Model.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Kuaiji: the First Chinese Accounting Large Language Model

Reference 29

Resolution
verified exact
local_arxiv, observed 2026-08-08T17:32:00.234005Z

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=arxiv_source observed=2026-08-08T17:31:59.849273Z digest=sha256:5bf8abbfa1922d1a2fa3228bfb8f5f81b8c1ffd671db955cdeca504c8dc0cd8c

Observation 25960b7c-3f1e-4010-b469-52d0a7dfbc28 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.852410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.852410Z digest=sha256:dcb7e4c3c0f5d28341ca0db898dcce2c3ae66e0904b326ebfce1569493065a40

Observation 397fd5d1-786b-4a54-bb40-3aa001d159e3 · outbound

This paper cites GPT-4 Technical Report.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation GPT-4 Technical Report

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.855783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.855783Z digest=sha256:08561e8e0a15b8afd94a908627be03a407207fbccfc4be88c9caf78132889f11

Observation 4c1cc5c3-ed39-405e-9f49-0550080fb395 · outbound

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

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Training language models to follow instructions with human feedback

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:32:00.468362Z

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=arxiv_source observed=2026-08-08T17:31:59.858796Z digest=sha256:853dfc1a8578880a5ac9abf607539b5f9949080220fbb4bb0c0c0562deb9b74e

Observation cc7f3b43-1bf4-409a-9bdb-0e9295edce31 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 33

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.459322Z

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=arxiv_source observed=2026-08-08T17:31:59.862499Z digest=sha256:8fb6d9e70e33d2f0440d7332fcec869d412e7588a9e63b42a883d0b29d093e7d

Observation 7750d40b-369a-4ba5-b095-73d5dae974dc · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.451318Z

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=arxiv_source observed=2026-08-08T17:31:59.866717Z digest=sha256:25c15016f53ebf0b020d9b0337b962b5c125b90b62b54ebeb1dceed561871ad8

Observation f8865962-6189-4098-a9de-b200789aee2a · outbound

This paper cites Identifying Semantic Induction Heads to Understand In-Context Learning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Identifying Semantic Induction Heads to Understand In-Context Learning

Reference 35

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unresolved
no resolver link, observed 2026-08-08T17:31:59.869479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.869479Z digest=sha256:86796bf4bd2c4ac4ac414b647e9c7410a3fc631c81179a1ff30dc6d887b1270e

Observation f4d1cefa-0a74-4185-9aad-9a37d29062d8 · outbound

This paper cites Learning or Self-aligning? Rethinking Instruction Fine-tuning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Learning or Self-aligning? Rethinking Instruction Fine-tuning

Reference 36

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unresolved
no resolver link, observed 2026-08-08T17:31:59.872964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.872964Z digest=sha256:d5373267d9bec9847ab238d5ed1476691bbd42f1f01f6f8b5a1a72e8d5f5daa7

Observation 65f3cb4c-1b59-4f7e-b1bc-d7bbeb5920f2 · outbound

This paper cites Learning Dynamics of LLM Finetuning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Learning Dynamics of LLM Finetuning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.876018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.876018Z digest=sha256:77480c0db0338d8fae04b7f16ba798085c1860185454e23079dbdb35f225b805

Observation 7066f076-15fe-4743-a4dc-7c2835b23a56 · outbound

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

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.879702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.879702Z digest=sha256:ddcd359d690f7c05358478b09ca4dc4463b4bca5bd3e004b44115ad066240159

Observation dfe3773f-abb7-4a73-9c47-d90c3ee23680 · outbound

This paper cites The Art of Defending: A Systematic Evaluation and Analysis of LLM Defense Strategies on Safety and Over-Defensiveness.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation The Art of Defending: A Systematic Evaluation and Analysis of LLM Defense Strategies on Safety and Over-Defensiveness

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.882927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.882927Z digest=sha256:6d929c0327e85fc0d98dd972cb5f15183a0925fd0e105d9b31611c7aaa746432

Observation 54c2efaf-0d3d-4cb5-985e-80c3d9a9097b · outbound

This paper cites GPTVoiceTasker: Advancing Multi-step Mobile Task Efficiency Through Dynamic Interface Exploration and Learning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation GPTVoiceTasker: Advancing Multi-step Mobile Task Efficiency Through Dynamic Interface Exploration and Learning

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.886209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.886209Z digest=sha256:00ed857186bd5e5dd278fa552381a295ce76e0eecfa98cb396f96489d49a1eaf

Observation aafbbff8-f7fc-4085-b8bb-09e499b67b8c · outbound

This paper cites Knowledge Verification to Nip Hallucination in the Bud.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Knowledge Verification to Nip Hallucination in the Bud

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.890019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.890019Z digest=sha256:5f8b8f986788a47d5525c4ed61ea1e1ed49147403a99e3a30c534347c5f20745

Observation f22eb664-662e-4ebd-97df-30ff5b35a66c · outbound

This paper cites Uncertainty Aware Learning for Language Model Alignment.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Uncertainty Aware Learning for Language Model Alignment

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.893923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.893923Z digest=sha256:f51bfe4049613020e9266afd1914822d0802a0f51fb69d2cc84292ab6b8b3cc7

Observation a11969d5-99cc-4bb6-bc41-ced495ba74b8 · outbound

This paper cites Know your limits: A survey of abstention in large language models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Know your limits: A survey of abstention in large language models

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T17:32:00.440937Z

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=arxiv_source observed=2026-08-08T17:31:59.897256Z digest=sha256:024c7805fb386c9c9d608143b31121bb05a1a35d29882a3fa51189ec09ef8084

Observation 7203753f-3149-4d15-bb44-1ec0e10bbe41 · outbound

This paper cites Do Llamas Work in English? On the Latent Language of Multilingual Transformers.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Do Llamas Work in English? On the Latent Language of Multilingual Transformers

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.899901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.899901Z digest=sha256:369c8a48aafb6b741b4bfcefa38c30e1e70c4ee31f39e5b949acdcf1e25cbca6

Observation f22ed801-3d0a-4800-ab1f-77523a0e600e · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.902481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.902481Z digest=sha256:7981b24f7f8924dfd83489c08e0d577df28dab1b78d1407a8011d8e7dcf748e4

Observation 11ccd4aa-1365-4999-b946-c001122c4f81 · outbound

This paper cites LESS: Selecting Influential Data for Targeted Instruction Tuning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation LESS: Selecting Influential Data for Targeted Instruction Tuning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.904624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.904624Z digest=sha256:c77f589292e046140caa883fcceb707ce4514c19966ffcde9295344cfc76626a

Observation 7664ad69-dbd1-4a3c-b4f9-f1cd953e8518 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.430316Z

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=arxiv_source observed=2026-08-08T17:31:59.907728Z digest=sha256:c04e0bb7d4c80956f6a0d7e961bef93507b709d880d44862c064889a89a6d785

Observation a99bae8a-575c-4940-ac76-c709c416c0ae · outbound

This paper cites Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.910590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.910590Z digest=sha256:5bbd96c7887936b9117d6c31e14a6b39ed8593c7919c1a37c16b597daaf06b69

Observation fc5bfc07-519f-404d-9dbc-fabd1755de94 · outbound

This paper cites Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-08-08T17:32:00.046467Z

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=arxiv_source observed=2026-08-08T17:31:59.913443Z digest=sha256:17f7691092fbb1529022e848d4183028506c9440a60eb6ee568481add24e805e

Observation 12886857-c64a-46bf-bb63-0f7df68c5661 · outbound

This paper cites SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.916976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.916976Z digest=sha256:fde8f6f7f77d408ad95bffeb982a24beb44b73a77f1c8e1210e3db2a0f20b14d

Observation 27cadcd8-87f4-4fdb-8557-e5daf82216dd · outbound

This paper cites Alignment for Honesty.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Alignment for Honesty

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.920040Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.920040Z digest=sha256:f4ca614843084e1e0856240f1ba1ff29f46588686dc43aea0820dff5577267f0

Observation 93b4e325-2e03-4e26-87a0-b2cd9d336945 · outbound

This paper cites xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.923195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.923195Z digest=sha256:4060e9849d03e9ff59dbb428dfa735aecdb2abaed13b6c987c708ca8d0c59db4

Observation 873a2a21-b63a-4e57-9382-109f4d6f1500 · outbound

This paper cites Neuron-Level Knowledge Attribution in Large Language Models.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Neuron-Level Knowledge Attribution in Large Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.926169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.926169Z digest=sha256:37a586480ef6fe0c0ba8b4f7e9a4eb4d00b6aff91b8375c5c09118f04e10fbfb

Observation 67d847bb-b7db-4638-bd13-7edf1ba7dc52 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.929482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.929482Z digest=sha256:38b0c78ee5ff52cc3e061e613a8803003003e65278caf17c4d02c3aa03c4def5

Observation f993a29d-7435-4afa-8b80-77269f7066e6 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.415351Z

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=arxiv_source observed=2026-08-08T17:31:59.932468Z digest=sha256:ac43255384b23583a6a051bb3dcb4886c726df6f1a81655a32c2e0e26c62240f

Observation 447ebd98-c33a-494a-9478-a25c9a8450c5 · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.935038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.935038Z digest=sha256:037d860ecacad6547cd419d229238be892100690d14cf6ac16174ebff5b49715

Observation ab1fb5ae-d453-4cbb-b173-f9e0cd0da1c6 · outbound

This paper cites Dataset Condensation with Gradient Matching.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Dataset Condensation with Gradient Matching

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.938121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.938121Z digest=sha256:4ebfa30eb417dfc53ba1dd2d4be770420bf0cce439a8668b350bc9f0aad3fa23

Observation 27e868bd-7e2a-4925-ad71-684eed03445d · outbound

This paper cites an unresolved cited work.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-08T17:32:00.405884Z

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=arxiv_source observed=2026-08-08T17:31:59.941609Z digest=sha256:397c31857152d77527e8ac0223cf1b253500050eb874acca98add8dde185edff

Observation 407f7128-254f-49bd-9c51-ffdb39be292e · outbound

This paper cites Utilize the Flow before Stepping into the Same River Twice: Certainty Represented Knowledge Flow for Refusal-Aware Instruction Tuning.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation Utilize the Flow before Stepping into the Same River Twice: Certainty Represented Knowledge Flow for Refusal-Aware Instruction Tuning

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-08-08T17:31:59.995292Z

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=arxiv_source observed=2026-08-08T17:31:59.945283Z digest=sha256:4237169b32755ff0813a7d30200aa1902d86ab552de3d5b2feaab1fd0a9b9666

Observation c254be1d-af1e-49de-b343-610620c637ca · outbound

This paper cites online" 'onlinestring :=.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation online" 'onlinestring :=

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.948359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.948359Z digest=sha256:20e87abb184f55558196b27a513b7f4ddcff5c3cc3891557a9dd61d14b3faa6c

Observation 902c6faa-59bb-49be-b97e-97d82bd793b9 · outbound

This paper cites write newline.

GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation write newline

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-08T17:31:59.951364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T17:31:59.951364Z digest=sha256:af6fe32a96be4c4ffd56e151628c0b8865414a16b0954a6b9e5b736cdee42b39

Pith citing papers

Observation 1e66bb30-e92b-406d-84a9-65e7d7589ac1 · inbound

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation cites this paper.

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation GRAIT: Gradient-Driven Refusal-Aware Instruction Tuning for Effective Hallucination Mitigation

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:25:34.981249Z

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=arxiv_source observed=2026-05-18T01:23:01.921132Z digest=sha256:9c7e9ab91b94d7b6fe953b88680e9089fb47fddbc9caef1127fb83b4814e3062