mlsanityData to 14 Oct 2026

Spoken Language Understanding on Unseen Tasks With In-Context Learning

arXiv 2505.07731 ↗First posted 12 May 2025cs.CL cs.LG eess.AScited by 2

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Abstract (arXiv)

Spoken language understanding (SLU) tasks involve diverse skills that probe the information extraction, classification and/or generation capabilities of models. In this setting, task-specific training data may not always be available. While traditional task-specific SLU models are unable to cater to such requirements, the speech-text large language models (LLMs) offer a promising alternative with emergent abilities. However, out of-the-box, our evaluations indicate that the zero/few-shot performance of prominent open-source speech-text LLMs on SLU tasks are not up to the mark. In this paper, we introduce a novel approach to robust task-agnostic fine-tuning using randomized class labels. With this proposed fine-tuning, we illustrate that the performance of the speech-text LLMs on an unseen task is significantly improved over standard approaches. Critically, the proposed approach avoids the requirement of task-specific data annotations for enabling new tasks in speech-text LLMs.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 32 of its 36 references that are in the map. First posted on arXiv 12 May 2025.

Builds on

32 of 36 references.

References · 32

  1. 2020Language Models are Few-Shot Learnerscited by 32,419
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2022Flamingo: a Visual Language Model for Few-Shot Learningcited by 4,386
  4. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,434
  5. 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
  6. 2023SALMONN: Towards Generic Hearing Abilities for Large Language Modelscited by 506
  7. 2021MetaICL: Learning to Learn In Contextcited by 454
  8. 2019Speech Model Pre-training for End-to-End Spoken Language Understandingcited by 193
  9. 2023Mitigating Label Biases for In-context Learningcited by 89
  10. 2023UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluationcited by 75
  11. 2023Symbol tuning improves in-context learning in language modelscited by 75
  12. 2021SLUE: New Benchmark Tasks for Spoken Language Understanding Evaluation on Natural Speechcited by 72
20 more
  1. 2024In-context Learning with Retrieved Demonstrations for Language Models: A Surveycited by 70
  2. 2024Many-Shot In-Context Learning in Multimodal Foundation Modelscited by 67
  3. 2021Earnings-21: A Practical Benchmark for ASR in the Wildcited by 62
  4. 2021ESPnet-SLU: Advancing Spoken Language Understanding through ESPnetcited by 53
  5. 2023Visual Instruction Tuning with Polite Flamingocited by 38
  6. 2022SLUE Phase-2: A Benchmark Suite of Diverse Spoken Language Understanding Taskscited by 35
  7. 2023Can Whisper perform speech-based in-context learning?cited by 35
  8. 2023COSMIC: Data Efficient Instruction-tuning For Speech In-Context Learningcited by 31
  9. 2023Instruction-following Evaluation through Verbalizer Manipulationcited by 30
  10. 2024Towards Multimodal In-Context Learning for Vision & Language Modelscited by 25
  11. 2019Speech Sentiment Analysis via Pre-trained Features from End-to-end ASR Modelscited by 21
  12. 2023Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understandingcited by 21
  13. 2022A Study on the Integration of Pre-trained SSL, ASR, LM and SLU Models for Spoken Language Understandingcited by 18
  14. 2021End-to-End Spoken Language Understanding for Generalized Voice Assistantscited by 17
  15. 2024BGE Landmark Embedding: A Chunking-Free Embedding Method For Retrieval Augmented Long-Context Large Language Modelscited by 15
  16. 2024Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Taskscited by 13
  17. 2024Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?cited by 11
  18. 2018Lexico-acoustic Neural-based Models for Dialog Act Classificationcited by 8
  19. 2023Zero-Shot End-to-End Spoken Language Understanding via Cross-Modal Selective Self-Trainingcited by 5
  20. 2023Exploring In-Context Learning of Textless Speech Language Model for Speech Classification Taskscited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Exploring Fine-Tuning of Large Audio Language Models for Spoken Language Understanding under Limited Speech Datacited by 6
  2. 2026In-Context Adaptation of Encoder-Decoder Models in Speech Recognitioncited by 0