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Paper Citation Record · LEDGER

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2501.00039.

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

pith.paper-citation-record.v1
2501.00039 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:37:43.712432Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

35 of 35 outbound references displayed

  • verified exact2
  • verified fuzzy9
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5b63fad4-9c5e-459f-bd50-b92c3813cfc1 · outbound

This paper cites The Llama 3 Herd of Models.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning The Llama 3 Herd of Models

Reference 1

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Observation bacb8168-7c84-48b4-b96f-e5985e267623 · outbound

This paper cites PaliGemma: A versatile 3B VLM for transfer.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning PaliGemma: A versatile 3B VLM for transfer

Reference 2

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Observation fa5dfc98-aad5-4bbe-9d94-eb030693769f · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 3

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Observation 55b79998-d6db-4aee-909c-491448a112ee · outbound

This paper cites Visual instruction tuning,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Visual instruction tuning,

Reference 4

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Observation 790dc13b-114f-4428-9a55-fd60acbbd6bd · outbound

This paper cites SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities

Reference 5

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source=pdf_text observed=2026-08-11T04:37:43.570480Z digest=sha256:660c1709b957082f025e4cc387f6a1290621b172a1874e314e2a2a452eaa0055

Observation 6de8fffe-199d-4ac2-922d-ee5cd397be97 · outbound

This paper cites AudioPaLM: A Large Language Model That Can Speak and Listen.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning AudioPaLM: A Large Language Model That Can Speak and Listen

Reference 6

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Observation 0ea3aa56-9b68-4d8e-9070-99c0803582ca · outbound

This paper cites Prompting large language models with speech recognition abilities,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Prompting large language models with speech recognition abilities,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 593741ac-6b5b-4bac-8e19-394753a912fe · outbound

This paper cites Large- scale language model rescoring on long-form data,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Large- scale language model rescoring on long-form data,

Reference 8

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source=pdf_text observed=2026-08-11T04:37:43.585716Z digest=sha256:513c69c9a894b2ddeff53403cf595a7a81e7fcff3270a626eecd25d3edefcf2b

Observation 1c49b68f-1b25-450d-8d16-01d100ea34a0 · outbound

This paper cites Adapting gpt, gpt-2 and bert language models for speech recognition,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Adapting gpt, gpt-2 and bert language models for speech recognition,

Reference 9

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 078ca27c-9dca-491b-8415-b64c9fe38552 · outbound

This paper cites Rescorebert: Discriminative speech recog- nition rescoring with bert,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Rescorebert: Discriminative speech recog- nition rescoring with bert,

Reference 10

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 9ed696b6-1258-47ee-9f46-0c62ccb8be1b · outbound

This paper cites On decoder-only architecture for speech-to-text and large language model integration,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning On decoder-only architecture for speech-to-text and large language model integration,

Reference 11

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source=pdf_text observed=2026-08-11T04:37:43.599631Z digest=sha256:e38c9748dfdcc1699de6257783d13d4daa0f09f2104e04dde40621e2a1c7ad70

Observation 8b07a1cf-c006-4967-be64-5fd4e3536c5a · outbound

This paper cites An Embarrassingly Simple Approach for LLM with Strong ASR Capacity.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning An Embarrassingly Simple Approach for LLM with Strong ASR Capacity

Reference 12

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Observation a051fe1c-1538-4e3e-af1a-e817a4acc30c · outbound

This paper cites Assessing ASR Model Quality on Disordered Speech using BERTScore.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Assessing ASR Model Quality on Disordered Speech using BERTScore

Reference 13

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source=pdf_text observed=2026-08-11T04:37:43.608978Z digest=sha256:9c881943fbc38fc1dac6a65ff6b9d6815b85548634f3c7732bb1d4b074419861

Observation 7fb3fb43-bacd-48bc-af1a-2e61f0ab736d · outbound

This paper cites Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Semantic Distance: A New Metric for ASR Performance Analysis Towards Spoken Language Understanding

Reference 14

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source=pdf_text observed=2026-08-11T04:37:43.613765Z digest=sha256:9dca8a9beabe30a4081d8e22b4ca889a1bb3b9f8d7b501098cafdeafb45fbf49

Observation 6c6469a6-7ae4-41ec-81ea-2ff839bf8e70 · outbound

This paper cites Clinical BERTScore: An Improved Measure of Automatic Speech Recognition Performance in Clinical Settings.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Clinical BERTScore: An Improved Measure of Automatic Speech Recognition Performance in Clinical Settings

Reference 15

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 25d07bfe-9a6e-42f8-a51c-c305ca521a48 · outbound

This paper cites Large language models as a proxy for human evaluation in assessing the comprehensibility of disordered speech transcription,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Large language models as a proxy for human evaluation in assessing the comprehensibility of disordered speech transcription,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T04:37:43.623099Z digest=sha256:5f674a546afccc36d00702abba1a9833da443ffcc97ed38ebdc77d8cb9056f53

Observation c068aa08-0391-4468-8675-10bac49321f8 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning BERTScore: Evaluating Text Generation with BERT

Reference 17

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Observation d1f3a5a7-2b51-4fb2-b6af-984422fe9d00 · outbound

This paper cites SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Reference 18

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source=pdf_text observed=2026-08-11T04:37:43.631679Z digest=sha256:ca51148a5f4b755c79bcfd5be57af6f8d5346c64db4e9b650e8bb39a31098d07

Observation d52aa861-c76c-4501-8234-3927ac842b96 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 19

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source=pdf_text observed=2026-08-11T04:37:43.636183Z digest=sha256:7f8633b203bc89e7d5b90d73e951ed8a7c68771557c95a2ff6b9eadbea81cd4e

Observation 8ff57ad9-efa4-441f-926d-0ead4ae47bcc · outbound

This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Reference 20

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source=pdf_text observed=2026-08-11T04:37:43.641130Z digest=sha256:568f83c589fa0ce56ac60b318be850a8234ed761877313f5d8b52fb8bcbd5b9c

Observation 647d54a2-b27c-4171-8e1d-1749c74059ea · outbound

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

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Gemma: Open Models Based on Gemini Research and Technology

Reference 21

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Observation 01dd0d97-e182-48f3-b2d2-0a1c6e8d040d · outbound

This paper cites Attention Is All You Need.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Attention Is All You Need

Reference 22

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source=pdf_text observed=2026-08-11T04:37:43.651395Z digest=sha256:796b193d5f2d0a9300437af5a1de3ca06a17ddd57065500c2dd2a1b2e6619db0

Observation dda1dd8c-ceb9-47cd-b132-51b7fff6bb24 · outbound

This paper cites Fast Transformer Decoding: One Write-Head is All You Need.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Fast Transformer Decoding: One Write-Head is All You Need

Reference 23

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Observation 1bcfa2df-5901-480d-b72f-79af7642a9ee · outbound

This paper cites Librispeech: An asr corpus based on public domain audio books,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Librispeech: An asr corpus based on public domain audio books,

Reference 24

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Observation 4f183117-25a4-415c-973e-9a0c34d3a8f2 · outbound

This paper cites Disordered speech data collection: Lessons learned at 1 million utterances from project euphonia.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Disordered speech data collection: Lessons learned at 1 million utterances from project euphonia

Reference 25

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T04:37:43.665661Z digest=sha256:e0cb6fcd3851fe6efdeb4b742cd0c7bb241febd0f084f882d61a1231af860ebe

Observation f0a82d79-8c48-42da-a019-3f28f8194a70 · outbound

This paper cites Au- tomatic speech recognition of disordered speech: Personalized models outperforming human listeners on short phrases.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Au- tomatic speech recognition of disordered speech: Personalized models outperforming human listeners on short phrases

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5716e530-6845-48b8-aabe-54f8ef929d2a · outbound

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

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Training language models to follow instructions with human feedback,

Reference 27

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Observation d4f8a2d8-a599-40e0-a105-cdbeb8b1b93e · outbound

This paper cites Automatic speech recog- nition of conversational speech in individuals with disordered speech,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Automatic speech recog- nition of conversational speech in individuals with disordered speech,

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 26400659-40c8-4a9f-93dc-d29f51350340 · outbound

This paper cites Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking

Reference 29

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Observation 76e697c4-79f2-4b76-90ef-7f4fbee55be4 · outbound

This paper cites Scaling laws for reward model overoptimization,.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Scaling laws for reward model overoptimization,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T04:37:43.688584Z digest=sha256:82f060afecb746c973d03337ae0c85269873ec3832834b6b5e547d8a153a278b

Observation 4faea8dc-623a-425c-b84a-d15495a440aa · outbound

This paper cites Reward Gaming in Conditional Text Generation.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Reward Gaming in Conditional Text Generation

Reference 31

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source=pdf_text observed=2026-08-11T04:37:43.692891Z digest=sha256:2e010d1ad4ce7de03cf5b0c572c02561ca6b2b88c9ebca2b5e8a228029e31264

Observation 7f4a72c2-4579-406e-9786-47ad96cedb5e · outbound

This paper cites Transforming and Combining Rewards for Aligning Large Language Models.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Transforming and Combining Rewards for Aligning Large Language Models

Reference 32

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source=pdf_text observed=2026-08-11T04:37:43.697884Z digest=sha256:c9bf09b811f8a061313f6321f9c39dc5f936343d94657d255636e22d98b0ae8b

Observation e3122e36-6e2e-45af-b66a-294be3db24d1 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 33

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source=pdf_text observed=2026-08-11T04:37:43.702896Z digest=sha256:1ae9f87ebd7a26300bc565f24277e54e17af40466fd1dd8cd1aebd7e34392bab

Observation fa21228b-ce79-42c9-84ce-0697de9c81ed · outbound

This paper cites Mixtral of Experts.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Mixtral of Experts

Reference 34

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source=pdf_text observed=2026-08-11T04:37:43.707737Z digest=sha256:e38e6dff0449872e52c4cef6477db9f112badc2243d95473a452bb54917cd972

Observation c642fc75-367e-4403-a5e8-60786b7e944c · outbound

This paper cites Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code.

Speech Recognition With LLMs Adapted to Disordered Speech Using Reinforcement Learning Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code

Reference 35

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local_arxiv, observed 2026-08-11T04:37:43.758490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Pith citing papers

No inbound Pith citation observations are available.