collaborators

7 papers

cs.AI2026

Oilbird: Training-Free Speculative Decoding with Keys the Verifier Already Computes

Tao Jin, Phuong Minh Nguyen, Zhenzhu Yan +2

Training-free speculative decoding drafts by matching an exact suffix of the context against a pool of earlier context. That lookup misses correct drafts already in the pool, most…

eess.AS2026

X-OPD: Cross-Modal On-Policy Distillation for Capability Alignment in Speech LLMs

Di Cao, Dongjie Fu, Hai Yu +3

While the shift from cascaded dialogue systems to end-to-end (E2E) speech Large Language Models (LLMs) improves latency and paralinguistic modeling, E2E models often exhibit a sign…

cs.AI2026

The Latent Space: Foundation, Evolution, Mechanism, Ability, and Outlook

Xinlei Yu, Zhangquan Chen, Yongbo He +36

Latent space is rapidly emerging as a native substrate for language-based models. While modern systems are still commonly understood through explicit token-level generation, an inc…

q-fin.RM2026

A Certified Higher Order Quantum Framework for CSA and Margin-Aware Collateral Optimization

Tao Jin, Stuart Florescu

Collateral allocation for uncleared derivatives is a legally constrained and operationally discrete optimization problem. Institutions must satisfy margin requirements while respec…

cs.CL2026

Goose: Anisotropic Speculation Trees for Training-Free Speculative Decoding

Tao Jin, Phuong Minh Nguyen, Naoya Inoue

Speculative decoding accelerates large language model inference by drafting multiple candidate tokens and verifying them in a single forward pass. Candidates are organized as a tre…

cs.IR2025

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval

Ruofan Hu, Yan Xia, Minjie Hong +5

Multimodal large language models (MLLMs) have seen substantial progress in recent years. However, their ability to represent multimodal information in the acoustic domain remains u…