Paper Citation Record · LEDGER

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2606.10838.

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

pith.paper-citation-record.v1
2606.10838 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T11:35:16.646773Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T11:35:16.646773Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T07:57:44.596905Z

Reference resolution

41 of 41 outbound references displayed

verified exact2
verified fuzzy0
unresolved36
parse uncertain0
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metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation acd5e373-7857-4386-bbf5-07fba0ae9dfb · outbound

This paper cites Therefore, research is shifting to- wards adaptation of pre-trained large language models (LLM) for speech recognition and understanding.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Therefore, research is shifting to- wards adaptation of pre-trained large language models (LLM) for speech recognition and understanding

Reference 1

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Observation 9a1743c7-d57e-4f03-85a2-1688951c6e5f · outbound

This paper cites Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains

Reference 2

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Observation 7b8adb40-daff-40b0-aa79-2917692a0321 · outbound

This paper cites audio-only.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains audio-only

Reference 3

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Observation e381f047-59fc-4796-962b-7e8ea919df76 · outbound

This paper cites use the context.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains use the context

Reference 4

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Observation ea0d76a0-27a8-4635-a2bf-8e2a1e38a3f7 · outbound

This paper cites Hence, we should not expect massive WER improvements, especially when segments are rather short.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Hence, we should not expect massive WER improvements, especially when segments are rather short

Reference 5

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Observation 8a1e48c3-bcee-4131-a022-dd9ca0bbaba1 · outbound

This paper cites We also introduced a pipeline and dataset that pair metadata with contextual transcript errors and correction rationales.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains We also introduced a pipeline and dataset that pair metadata with contextual transcript errors and correction rationales

Reference 6

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Observation f784c8bd-53c0-4df0-a516-049f0f4a5b85 · outbound

This paper cites an unresolved cited work.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Unresolved cited work

Reference 7

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Observation 020b58d4-090a-4f0c-9044-9173d43025b2 · outbound

This paper cites No part of the manuscript’s content or ideas was produced by generative AI.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains No part of the manuscript’s content or ideas was produced by generative AI

Reference 8

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Observation d165279a-20bc-4274-9b35-5125fdcb84b0 · outbound

This paper cites Robust speech recognition via large-scale weak su- pervision,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Robust speech recognition via large-scale weak su- pervision,

Reference 9

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Observation eab2204e-8c00-4b1b-a18f-9702595a57b3 · outbound

This paper cites OWSM v4: Improving open whisper-style speech models via data scaling and cleaning,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains OWSM v4: Improving open whisper-style speech models via data scaling and cleaning,

Reference 10

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Observation b4342c52-138b-495d-b4d1-540952a43f17 · outbound

This paper cites Less is more: Accu- rate speech recognition & translation without web-scale data,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Less is more: Accu- rate speech recognition & translation without web-scale data,

Reference 11

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Observation d455614f-ef5a-47f3-85ea-c30083f859f0 · outbound

This paper cites Contextualized end-to-end automatic speech recognition with intermediate bias- ing loss,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Contextualized end-to-end automatic speech recognition with intermediate bias- ing loss,

Reference 12

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Observation 223b4596-07f9-4cc7-abdb-33ed92d9db3f · outbound

This paper cites BR- ASR: Efficient and scalable bias retrieval framework for contex- tual biasing ASR in speech LLM,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains BR- ASR: Efficient and scalable bias retrieval framework for contex- tual biasing ASR in speech LLM,

Reference 13

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Observation 33b18c3a-27f2-443e-a7ee-7ed0964e4051 · outbound

This paper cites Contextual biasing speech recognition in speech-enhanced large language model,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Contextual biasing speech recognition in speech-enhanced large language model,

Reference 14

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Observation 1e4361a6-2b13-4d4a-ae45-1ba3897b0215 · outbound

This paper cites Improving domain-specific ASR with LLM-generated contextual descriptions,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Improving domain-specific ASR with LLM-generated contextual descriptions,

Reference 15

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Observation 89c05a2f-3aad-4286-b1f4-ef00acaee108 · outbound

This paper cites MaLa- ASR: Multimedia-assisted LLM-based ASR,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains MaLa- ASR: Multimedia-assisted LLM-based ASR,

Reference 16

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Observation 802a4f8d-684f-40f1-bd6f-74c85405b212 · outbound

This paper cites Contextual biasing of named-entities with large lan- guage models,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Contextual biasing of named-entities with large lan- guage models,

Reference 17

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Observation a85f323b-93d5-4371-b69e-de5908bdb9e2 · outbound

This paper cites Listen again and choose the right answer: A new paradigm for automatic speech recognition with large language models,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Listen again and choose the right answer: A new paradigm for automatic speech recognition with large language models,

Reference 18

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Source-reported events for the cited work

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Observation 3db1e8d5-4731-406e-999a-4f36eda89892 · outbound

This paper cites Towards interfacing large language models with asr systems using confidence measures and prompting,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Towards interfacing large language models with asr systems using confidence measures and prompting,

Reference 20

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Observation 87c3bb3f-1cff-4a71-8c80-5be085830b21 · outbound

This paper cites Predicting compact phrasal rewrites with large language models for ASR post edit- ing,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Predicting compact phrasal rewrites with large language models for ASR post edit- ing,

Reference 21

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Observation cefe8e71-cb86-42f0-8935-72eda160ebac · outbound

This paper cites Chain-of-thought prompting elic- its reasoning in large language models,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Chain-of-thought prompting elic- its reasoning in large language models,

Reference 22

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Observation 85227b8a-768c-43ce-aea9-730a1382386f · outbound

This paper cites Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes,

Reference 23

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Observation a323edff-fbb5-404f-a8a7-d13e1c1228c0 · outbound

This paper cites Speech recognition rescoring with large speech-text foundation models,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Speech recognition rescoring with large speech-text foundation models,

Reference 24

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Observation 9259eaa1-fe73-416a-898d-290458286e7b · outbound

This paper cites Phonetically-augmented discriminative rescoring for voice search error correction,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Phonetically-augmented discriminative rescoring for voice search error correction,

Reference 25

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Observation 68dde5ba-dfa9-4e03-8391-48a514d37a25 · outbound

This paper cites SALSA: Speedy ASR-LLM synchronous aggregation,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains SALSA: Speedy ASR-LLM synchronous aggregation,

Reference 26

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Observation 545d17d0-bfff-41fb-acd5-a98076934f6c · outbound

This paper cites Skip-Salsa: Skip synchronous fusion of ASR LLM de- coders,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Skip-Salsa: Skip synchronous fusion of ASR LLM de- coders,

Reference 27

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Observation 35eda3da-a87d-4dcb-8e26-e4993f24c6de · outbound

This paper cites SAKURA: On the multi-hop reasoning of large audio-language models based on speech and audio information,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains SAKURA: On the multi-hop reasoning of large audio-language models based on speech and audio information,

Reference 28

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Observation 686169e5-8eb6-4272-a024-a89dfb3179e7 · outbound

This paper cites MMAU: A mas- sive multi-task audio understanding and reasoning benchmark,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains MMAU: A mas- sive multi-task audio understanding and reasoning benchmark,

Reference 29

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Observation 2017c47c-82d9-43f0-a6f4-89138b205358 · outbound

This paper cites Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Audio-CoT: Exploring Chain-of-Thought Reasoning in Large Audio Language Model

Reference 30

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Observation 3e6019b8-a250-4d77-9ec6-2806549b1c65 · outbound

This paper cites Audio- reasoner: Improving reasoning capability in large audio language models,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Audio- reasoner: Improving reasoning capability in large audio language models,

Reference 31

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Observation 1e5b62ca-2395-481a-b670-fb09cca10408 · outbound

This paper cites Can large audio-language models truly hear? tackling hallucinations with multi-task assessment and stepwise audio reasoning,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Can large audio-language models truly hear? tackling hallucinations with multi-task assessment and stepwise audio reasoning,

Reference 32

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This paper cites DeSTA: Enhancing speech language mod- els through descriptive speech-text alignment,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains DeSTA: Enhancing speech language mod- els through descriptive speech-text alignment,

Reference 33

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This paper cites Developing instruction- following speech language model without speech instruction- tuning data,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Developing instruction- following speech language model without speech instruction- tuning data,

Reference 34

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This paper cites Desta2. 5-audio: Toward general-purpose large audio language model with self-generated cross-modal alignment.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains Desta2. 5-audio: Toward general-purpose large audio language model with self-generated cross-modal alignment

Reference 35

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Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains GAMA: A large audio-language model with advanced audio understanding and complex reasoning abilities,

Reference 36

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This paper cites GigaSpeech: An evolving, multi-domain ASR cor- pus with 10,000 hours of transcribed audio,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains GigaSpeech: An evolving, multi-domain ASR cor- pus with 10,000 hours of transcribed audio,

Reference 37

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This paper cites SlideSpeech: A large scale slide-enriched audio-visual corpus,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains SlideSpeech: A large scale slide-enriched audio-visual corpus,

Reference 38

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This paper cites SlideA VSR: A dataset of paper explanation videos for audio-visual speech recognition,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains SlideA VSR: A dataset of paper explanation videos for audio-visual speech recognition,

Reference 39

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This paper cites M 3A V: A multimodal, multigenre, and multi- purpose audio-visual academic lecture dataset,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains M 3A V: A multimodal, multigenre, and multi- purpose audio-visual academic lecture dataset,

Reference 40

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This paper cites BERT: Pre- training of deep bidirectional transformers for language under- standing,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains BERT: Pre- training of deep bidirectional transformers for language under- standing,

Reference 41

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This paper cites QLoRA: Efficient finetuning of quantized llms,.

Towards Deep Contextual Reasoning from Broad Descriptions for ASR with Speech-LLM via Metadata-Driven Reasoning Chains QLoRA: Efficient finetuning of quantized llms,

Reference 42

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Pith citing papers

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