arXiv subjects

Huan Shen

Publications and source records attributed to Huan Shen.

4 recordsLinked to original sources

arXiv2026

CoDeTT: A Context-Aware Decision Benchmark for Turn-Taking Evaluation

Turn-taking modeling is fundamental to spoken dialogue systems, yet its evaluation remains fragmented and often limited to binary boundary detection under narrow interaction settings. Such protocols hinder systematic comparison and obscure model weaknesses across conversational conditions. We present CoDeTT, a context-aware decision benchmark for turn-taking evaluation. CoDeTT formulates turn-taking as a structured decision problem and constructs a multi-scenario dataset with fine-grained decision categories and controlled context variations. Under a unified evaluation protocol, we assess representative existing models and observe substantial performance disparities across decision types and interaction scenarios. CoDeTT provides a standardized benchmark for systematic and context-aware evaluation of turn-taking systems. The benchmark dataset and evaluation toolkit are available at https://yingaowang-casia.github.io/CoDeTT.github.io/.

cs.SD↗

arXiv2026

CLAR: CIF-Localized Alignment for Retrieval-Augmented Speech LLM-Based Contextual ASR

Speech LLM-based ASR often struggles with named entities and long-tail words due to strong internal language-model priors. Retrieval-augmented biasing can help, but its effectiveness depends on accurate hotword localization in full-utterance speech under weak supervision. We propose CLAR, a dual-encoder speech-text retriever that uses Continuous Integrate-and-Fire (CIF) to learn monotonic token-level alignments without timestamps. With length-aware localized matching, CLAR anchors short-entity acoustic cues and reduces representation dilution and attention drift. The retriever is trained with a multi-granularity objective combining global and local segment-level contrastive losses and a CIF quantity constraint. At inference, top-ranked hotwords are injected as contextual prompts for the Speech LLM, improving recognition without shallow fusion. Experiments show that CLAR significantly improves hotword retrieval and reduces both CER and B-WER against strong contextual ASR baselines.

cs.SD↗

arXiv2025

Argo: An efficient verification framework for distributed in-network computing

Distributed in-network programs are increasingly deployed in data centers for their performance benefits, but shifting application logic to switches also enlarges the failure domain. Ensuring their correctness before deployment is thus critical for reliability. While prior verification frameworks can efficiently detect bugs for programs running on a single switch, they overlook the common interactive behaviors in distributed settings, thereby missing related bugs that can cause state inconsistencies and system failures. This paper presents Procurator, a verification framework that efficiently captures interactive behaviors in distributed in-network programs. Procurator introduces a formal model combining the actor paradigm with Communicating Sequential Processes (CSP), translating pipeline execution into reactive, event-driven actors and unifying their interactions as message passing. To support flexible specification of distributed properties, it provides a unified intent language. Additionally, it incorporates a semantic-aware state pruner to reduce verification complexity, thus ensuring system scalability. Evaluation results show that Procurator efficiently uncovers 10 distinct bugs caused by interactive behaviors across five real-world in-network systems. It also reduces verification time by up to 913.2x and memory consumption by up to 1.9x compared to the state-of-the-art verifier.

cs.NI↗

arXiv2018

Theoretical Analysis on Deflagration-to-Detonation Transition

The study on deflagration-to-detonation transition (DDT) is very important because this mechanism has relevance to safety issues in industries, where combustible premixed gases are in general use. However, the quantitative prediction of DDT is one of the major unsolved problems in combustion and detonation theory to date. In this paper, the DDT process is studied theoretically and the critical condition is given by a concise theoretical expression. The results show that a deflagration wave propagating with about 60% Chapman-Jouguet (C-J) detonation velocity is a critical condition. This velocity is the maximum propagating velocity of a deflagration wave and almost equal to the sound speed of combustion products. When this critical conation is reached, a C-J detonation is triggered immediately. This is the quantitative criteria of the DDT process.

physics.flu-dyn↗