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20242026
most citedPhi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

7 citations · 7 across the 13 of their papers we have counts for

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9 papers · 1 filter

eess.AS2026

Teaching LLMs to Hear Who Spoke What: Metadata-Supervised Pretraining for Encoder-Free Speech-LLMs

Mohan Shi, Ruchao Fan, Sunit Sivasankaran +2

Encoder-based speech large language models (Speech-LLMs) commonly employ pretrained speech encoders that prioritize linguistic content but may discard fine-grained acoustic cues es…

eess.AS2026

Compress the Cache, Not the Speech Embedding: KV Compression for Efficient Speech LLMs

Ke-Han Lu, Keqi Deng, Ruchao Fan +2

Speech large language models (Speech LLMs) typically encode speech into sequences far longer than text, creating a major efficiency bottleneck during autoregressive decoding. A com…

eess.AS2026

LLM can Read Spectrogram: Encoder-free Speech-Language Modeling

Ruchao Fan, Yiming Wang, Yuxuan Hu +6

Recent speech-aware large language models (Speech-LLMs) rely on pre-trained speech encoders to convert audio into semantic/acoustic rich representations consumable by LLM. In this…

eess.AS2026

Preserving Speech-to-Text LLM Capabilities in Speech-to-Speech Generation

Yuxuan Hu, Heng Lu, Ruchao Fan +8

Strong speech-to-text (S2T) LLMs already provide robust speech perception and text reasoning, but adding speech-to-speech (S2S) output is challenging: fine-tuning the backbone can…

eess.AS2026

RLBR: Reinforcement Learning with Biasing Rewards for Contextual Speech Large Language Models

Bo Ren, Ruchao Fan, Yelong Shen +2

Speech large language models (LLMs) have driven significant progress in end-to-end speech understanding and recognition, yet they continue to struggle with accurately recognizing r…

eess.AS2025

Train Short, Infer Long: Speech-LLM Enables Zero-Shot Streamable Joint ASR and Diarization on Long Audio

Mohan Shi, Xiong Xiao, Ruchao Fan +2

Joint automatic speech recognition (ASR) and speaker diarization aim to answer the question "who spoke what" in multi-speaker scenarios. In this paper, we present an end-to-end spe…

eess.AS2025

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model

Haibin Wu, Yuxuan Hu, Ruchao Fan +8

Speech language models (Speech LMs) enable end-to-end speech-text modeling within a single model, offering a promising direction for spoken dialogue systems. The choice of speech-t…

eess.AS2025

SLM-S2ST: A multimodal language model for direct speech-to-speech translation

Yuxuan Hu, Haibin Wu, Ruchao Fan +4

Speech-aware language models (LMs) have demonstrated capabilities in understanding spoken language while generating text-based responses. However, enabling them to produce speech o…

eess.AS2024

AlignFormer: Modality Matching Can Achieve Better Zero-shot Instruction-Following Speech-LLM

Ruchao Fan, Bo Ren, Yuxuan Hu +3

Integrating speech into LLM (speech-LLM) has gaining increased attention recently. The mainstream solution is to connect a well-trained speech encoder and LLM with a neural adapter…