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Paper Citation Record · LEDGER

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings

As of 9 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2509.04473.

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

pith.paper-citation-record.v1
2509.04473 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:53:26.333669Z

measured 37 of 37 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 2026-08-05T13:53:23.449877Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T13:53:27.421561Z

Reference resolution

36 of 36 outbound references displayed

  • verified exact4
  • verified fuzzy10
  • unresolved20
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4410ef93-6f9e-4d03-9ab9-5cba25ec4f97 · outbound

This paper cites SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:53:27.462666Z

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=pdf_text observed=2026-08-05T13:53:23.449877Z digest=sha256:9ea55870700004c4c68d1bda0127db86ab4d35fa3535c1f0772447b83d2c515b

Observation a3952895-eef2-48ee-b920-228e158814c9 · outbound

This paper cites an unresolved cited work.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-05T13:53:30.674755Z

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=pdf_text observed=2026-08-05T13:53:23.496997Z digest=sha256:94bf349f1139ed4c4d1ef33f52ac0de0554ed511c97263b8b08153786dddbdca

Observation 885256b4-b595-4d76-b1f4-82e21a0f4955 · outbound

This paper cites The ASR baseline benchmarks on the Librispeech dataset are derived from the study in [5], which is similar to ours but focuses solely on ASR.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings The ASR baseline benchmarks on the Librispeech dataset are derived from the study in [5], which is similar to ours but focuses solely on ASR

Reference 3

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T13:53:30.449286Z

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=pdf_text observed=2026-08-05T13:53:23.556198Z digest=sha256:05c2b5ce32ef7da7552decd64560f38f087d6f3da48e8dd3bb8fe1bcf9511208

Observation 732f7e07-3f18-4a56-993b-d8257f0d5638 · outbound

This paper cites We conduct the SA training for 50 epochs with a learning rate 5 ∗ 10−4, batch size 6, and a linear decay scheduler with 3000 warm-up steps.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings We conduct the SA training for 50 epochs with a learning rate 5 ∗ 10−4, batch size 6, and a linear decay scheduler with 3000 warm-up steps

Reference 4

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T13:53:30.190439Z

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=pdf_text observed=2026-08-05T13:53:23.611938Z digest=sha256:d586b2ca036619e98f2af3eabe0610a712a3a6083a8eafec2e11ede488feb5d8

Observation 8e497bb1-3157-479a-ae62-01fb49703981 · outbound

This paper cites The proposed model exhibits the capability to capture semantic meanings by effectively mapping speech features to text tokens that are interpretable by LLMs.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings The proposed model exhibits the capability to capture semantic meanings by effectively mapping speech features to text tokens that are interpretable by LLMs

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:29.960854Z

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=pdf_text observed=2026-08-05T13:53:23.666334Z digest=sha256:d4e25bae764ccfdeddcc0a9d9ea50d1f331167041c69782b91bb293cf1c4b4f7

Observation 72776b61-651b-458d-8e17-569f95cb25ea · outbound

This paper cites GPT-4 Technical Report.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings GPT-4 Technical Report

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:23.718934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:23.718934Z digest=sha256:cd7e45a9f7f2de9c16f02e3e441bcae968d7352b77122d804e6414cc9a66e751

Observation 4d98b71f-fc12-4dc9-84ee-1643e5b8089a · outbound

This paper cites A survey on speech large language models,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings A survey on speech large language models,

Reference 7

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no resolver link, observed 2026-08-05T13:53:23.783968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:23.783968Z digest=sha256:ed8bc2fd40f2d7d72f18c5035702363b8bdcdf81e752fd6cca0b8ab78531db06

Observation 781a65e3-df2f-4100-925e-febc9653236d · outbound

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

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Robust speech recognition via large-scale weak supervision,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:23.847695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:23.847695Z digest=sha256:29d7ecfda4d7f0ad20ee9dd58d26ace408e55a8d911818e30139484435930cee

Observation a61053b5-c086-41dd-ac0d-63fe788e99da · outbound

This paper cites TinyLlama: An Open-Source Small Language Model.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings TinyLlama: An Open-Source Small Language Model

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:23.880279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:23.880279Z digest=sha256:2289c370f5a91231352975340312f99abb604206306a156300c439944ee19a91

Observation 0a2508d2-110c-4be6-afcc-a424821966ce · outbound

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

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings An Embarrassingly Simple Approach for LLM with Strong ASR Capacity

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:23.962333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:23.962333Z digest=sha256:3ef2b58bd5828ad3524fea3be66468846a0a8c8fd1d73f7f78fcaefc881dc8ae

Observation 23427e32-03aa-4a5c-8c6e-7bfae1829283 · outbound

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

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.021157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.021157Z digest=sha256:9ffddd753c5fb024b80861eb307f40d627c3959a4e4c09b7b881b4fd3edc1f7d

Observation c422d072-d248-469c-8148-e8c47a873d02 · outbound

This paper cites SALMONN: Towards Generic Hearing Abilities for Large Language Models.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings SALMONN: Towards Generic Hearing Abilities for Large Language Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.084203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.084203Z digest=sha256:9e0f2e9697d26d41f2a589083dbaa874da6964553d7282e35785b7d9da692fa2

Observation 5bdd7516-15ca-4c7b-b5c4-84026c4896c1 · outbound

This paper cites Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.131210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.131210Z digest=sha256:21bfdbb9a888b5f8cea1d5df5fcf86a7e109558a5a03e23a658e7d95181e533c

Observation e8c6534f-ef50-4d68-aef2-43dc18d60de8 · outbound

This paper cites AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.189799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.189799Z digest=sha256:8f390df001c53bb4463c3fb87792e7d5f15e389f4a5f11a1a9957be380b96235

Observation de92ddd5-55ca-4b6b-a812-dc0c72dacf23 · outbound

This paper cites ” i’ve heard of you!.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings ” i’ve heard of you!

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:29.676823Z

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=pdf_text observed=2026-08-05T13:53:24.253256Z digest=sha256:4fa638d7a38496eaf6f55bbb71552d703d1556412583603f3ae106fc9749fe27

Observation 428a4dd6-40a7-4586-b460-2cf0ad19c3fb · outbound

This paper cites Whisper-slu: Ex- tending a pretrained speech-to-text transformer for low resource spoken language understanding,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Whisper-slu: Ex- tending a pretrained speech-to-text transformer for low resource spoken language understanding,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:29.415213Z

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=pdf_text observed=2026-08-05T13:53:24.315150Z digest=sha256:530be46b0c0b35644cedd27f4bfc242c25c54d355e731d98133c382af419a0da

Observation 50b75b74-679c-4de3-8a9b-7c016f811fb1 · outbound

This paper cites On the Evaluation of Speech Foundation Models for Spoken Language Understanding.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings On the Evaluation of Speech Foundation Models for Spoken Language Understanding

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.385057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.385057Z digest=sha256:a270bdbdb0d626b5dab931fb00f14de54fae062a724fa95e7e1a7b7a30650f13

Observation 7807b942-288e-4d33-8945-a4187e73c536 · outbound

This paper cites Universlu: Uni- versal spoken language understanding for diverse tasks with nat- ural language instructions,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Universlu: Uni- versal spoken language understanding for diverse tasks with nat- ural language instructions,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:29.176460Z

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=pdf_text observed=2026-08-05T13:53:24.404892Z digest=sha256:691c840189585e05f562a95e8c0eec79204684355c2774190b38326ca8488f0a

Observation cc3f337a-3a2d-429c-af5c-37935193ffbc · outbound

This paper cites Prompting Whisper for QA-driven Zero-shot End-to-end Spoken Language Understanding.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Prompting Whisper for QA-driven Zero-shot End-to-end Spoken Language Understanding

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:53:27.083579Z

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=pdf_text observed=2026-08-05T13:53:24.428503Z digest=sha256:0896fdb80783828a3d39a382137f17a1290e2a00025fa101d61fc2c2d6d4b99a

Observation 9dbc050f-12ae-42f1-a78a-099bbe3d5e2b · outbound

This paper cites Salm: Speech- augmented language model with in-context learning for speech recognition and translation,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Salm: Speech- augmented language model with in-context learning for speech recognition and translation,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:28.826670Z

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=pdf_text observed=2026-08-05T13:53:24.464158Z digest=sha256:7f07d2763410db9bb323fd2ba8dec67841f7bca0ad7c58b072957ba7aade9325

Observation 9533b423-310a-49f5-a200-f934b58dbf2c · outbound

This paper cites WhisperNER: Unified Open Named Entity and Speech Recognition.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings WhisperNER: Unified Open Named Entity and Speech Recognition

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:53:26.920380Z

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=pdf_text observed=2026-08-05T13:53:24.497567Z digest=sha256:ec07a2da58023ce73517c28850923131d4b5ea3d41eaf651bf2e50de3e4cbcee

Observation 3808f0ce-1201-4d6c-8054-6db1f7971421 · outbound

This paper cites Chinese asr and ner improvement based on whisper fine-tuning,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Chinese asr and ner improvement based on whisper fine-tuning,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:28.546140Z

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=pdf_text observed=2026-08-05T13:53:24.554685Z digest=sha256:a912b3cdeb633c82a00104cdff4ca3b61a70714bbbbd5c211d7b6094898c2b82

Observation 388e7e80-4436-4167-a6df-e22a9740a22f · outbound

This paper cites NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.614481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.614481Z digest=sha256:df5c954b4691637847e2348744cca514cc15e953d3565d9c2d77b8192fa60e49

Observation e9ac977e-bbb2-4630-b908-0fa832ec4f78 · outbound

This paper cites Using Large Language Model for End-to-End Chinese ASR and NER.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Using Large Language Model for End-to-End Chinese ASR and NER

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:53:26.745129Z

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=pdf_text observed=2026-08-05T13:53:24.724041Z digest=sha256:5c76dce833f2d9eba43254da4e079c1a9ae887922138fedba8cb4d08b9491470

Observation 9bf4cc41-8be5-499a-ab66-a0aa23b369a8 · outbound

This paper cites WavLLM: Towards Robust and Adaptive Speech Large Language Model.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings WavLLM: Towards Robust and Adaptive Speech Large Language Model

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.835833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.835833Z digest=sha256:feca6da59e053c16efe9f1af1501656c0d3367789a3bdbd18dea96eaf3538fd8

Observation 6aad7e48-dc54-4584-ae1d-e9607bda13ee · outbound

This paper cites End-to-end Named Entity Recognition from English Speech.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings End-to-end Named Entity Recognition from English Speech

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:24.953794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:24.953794Z digest=sha256:595b5dda129bedbc8a9cb8549b85b63e810ebb5c64a929a554de00fb85adfbfc

Observation 8f73a246-f793-410c-b515-54f69c5432dd · outbound

This paper cites End-to-end named entity and semantic concept extraction from speech,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings End-to-end named entity and semantic concept extraction from speech,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:28.260325Z

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=pdf_text observed=2026-08-05T13:53:25.081211Z digest=sha256:ffe849a7247a9fa070d68d0ffe9f1e1de481f0b7469db79542f2d9b7e9b290a9

Observation ab6ef9c1-2eb4-42b7-a572-417e22a4c48c · outbound

This paper cites Slue: New benchmark tasks for spoken language un- derstanding evaluation on natural speech,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Slue: New benchmark tasks for spoken language un- derstanding evaluation on natural speech,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:27.940309Z

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=pdf_text observed=2026-08-05T13:53:25.186661Z digest=sha256:4f2edb1a33e60b60a87d7dc600c8daecf89a980de446c16fbb0646dbbc666056

Observation 0c5dcb25-d6a4-4dd0-a158-e93b099c9ebe · outbound

This paper cites Lib- rispeech: an asr corpus based on public domain audio books,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Lib- rispeech: an asr corpus based on public domain audio books,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:27.780738Z

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=pdf_text observed=2026-08-05T13:53:25.322583Z digest=sha256:9666b821c23db9a515a22198cc14086f908391a999f8bc7d8e2d8fe4f12d29bf

Observation 1d292078-0891-4d23-92c2-4d347df25a3b · outbound

This paper cites VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:25.480535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:25.480535Z digest=sha256:0007f1050984303d6eb669ddb5be394c7ef3a4da6de385a836a46db7b3ee787c

Observation 85ece306-a343-488d-9b0b-d834a17db7bc · outbound

This paper cites VoxCeleb: a large-scale speaker identification dataset.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings VoxCeleb: a large-scale speaker identification dataset

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:25.645970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:25.645970Z digest=sha256:ebe31f2ea59995422235096796dc837d6ce6aa084aa7f661345b8794267d71eb

Observation b3972282-9234-49b3-8c18-48c3e205d0be · outbound

This paper cites Ontonotes: the 90% solution,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Ontonotes: the 90% solution,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T13:53:27.633245Z

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=pdf_text observed=2026-08-05T13:53:25.785734Z digest=sha256:67be7d839b1a13fe7cda5ba0bd0d0f7a67278f2caea421241d34e44cfd0db40d

Observation d8ada98e-7101-41aa-bc65-6b30936d052a · outbound

This paper cites PromptNER: Prompting For Named Entity Recognition.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings PromptNER: Prompting For Named Entity Recognition

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:25.913786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:25.913786Z digest=sha256:06896fecbe1a6ecf6bb5fe2b0c0dc5beebbece9b0c900cd9a270a4a1017567ea

Observation b98be2c8-d21e-49a4-9458-0ff433743321 · outbound

This paper cites Specaugment: A simple data augmentation method for automatic speech recognition,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Specaugment: A simple data augmentation method for automatic speech recognition,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:26.053496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:26.053496Z digest=sha256:2e6f371304d23513a64122cda483bfbab911c9130e180d98f41e3bfd581126f0

Observation 69c6d5fb-6e01-442b-b1ff-ec02188ae659 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings wav2vec 2.0: A framework for self-supervised learning of speech repre- sentations,

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:26.205888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:26.205888Z digest=sha256:b207366cbc3ba47d864c64ffb42ec4bd89274f2624b13293c171d1b3d395fd3c

Observation a0a3bb6a-f4c9-4e8b-8947-8f08906babb4 · outbound

This paper cites Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings Hubert: Self-supervised speech represen- tation learning by masked prediction of hidden units,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T13:53:26.333669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:53:26.333669Z digest=sha256:04c39e5c044983ba0098ac987c7308f71b057690a7d02d0a3c71ce871c2a7d67

Pith citing papers

Observation 4410ef93-6f9e-4d03-9ab9-5cba25ec4f97 · inbound

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings cites this paper.

SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings SpeechLLM: Unified Speech and Language Model for Enhanced Multi-Task Understanding in Low Resource Settings

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-05T13:53:27.462666Z

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=pdf_text observed=2026-08-05T13:53:23.449877Z digest=sha256:9ea55870700004c4c68d1bda0127db86ab4d35fa3535c1f0772447b83d2c515b