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20232026
most citedSpeechPrompt: Prompting Speech Language Models for Speech Processing Tasks

8 citations · 20 across the 23 of their papers we have counts for

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7 papers · 1 filter

cs.CL2025

BILLY: Steering Large Language Models via Merging Persona Vectors for Creative Generation

Tsung-Min Pai, Jui-I Wang, Li-Chun Lu +3

Multi-LLM systems enhance the creativity of large language models by simulating human collective intelligence but suffer from significant drawbacks, such as high computational cost…

eess.AS2025

Full-Duplex-Bench-v2: A Multi-Turn Evaluation Framework for Duplex Dialogue Systems with an Automated Examiner

Guan-Ting Lin, Shih-Yun Shan Kuan, Jiatong Shi +4

While full-duplex speech agents enable natural, low-latency interaction by speaking and listening simultaneously, their consistency and task performance in multi-turn settings rema…

eess.AS2025

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

Kai-Wei Chang, En-Pei Hu, Chun-Yi Kuan +7

Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of temporal dynamics, including the abil…

eess.AS2025

DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment

Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25

We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…

cs.CL2025

Analyzing Mitigation Strategies for Catastrophic Forgetting in End-to-End Training of Spoken Language Models

Chi-Yuan Hsiao, Ke-Han Lu, Kai-Wei Chang +3

End-to-end training of Spoken Language Models (SLMs) commonly involves adapting pre-trained text-based Large Language Models (LLMs) to the speech modality through multi-stage train…

eess.AS2025

SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning

Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4

We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…

cs.CL2025★ 3 cited

On The Landscape of Spoken Language Models: A Comprehensive Survey

Siddhant Arora, Kai-Wei Chang, Chung-Ming Chien +7

The field of spoken language processing is undergoing a shift from training custom-built, task-specific models toward using and optimizing spoken language models (SLMs) which act a…