Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing

Kavli Affiliate: Xiang Zhang | First 5 Authors: Xiang Zhang, Jiaqi Wei, Zijie Qiu, Sheng Xu, Nanqing Dong | Summary: Peptide sequencing-the process of identifying amino acid sequences from mass spectrometry data-is a fundamental task in proteomics. Non-Autoregressive Transformers (NATs) have proven highly effective for this task, outperforming traditional methods. Unlike autoregressive models, which generate […]


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Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models

Kavli Affiliate: Xiang Zhang | First 5 Authors: Zongyu Wu, Minhua Lin, Zhiwei Zhang, Fali Wang, Xianren Zhang | Summary: Large vision-language models (LVLMs) have demonstrated outstanding performance in many downstream tasks. However, LVLMs are trained on large-scale datasets, which can pose privacy risks if training images contain sensitive information. Therefore, it is important to […]


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The Throughput Gain of Hypercycle-level Resource Reservation for Time-Triggered Ethernet

Kavli Affiliate: Feng Wang | First 5 Authors: Peng Wang, Suman Sourav, Binbin Chen, Hongyan Li, Feng Wang | Summary: Time-Triggered Communication is a key technology for many safety-critical systems, with applications spanning the areas of aerospace and industrial control. Such communication relies on time-triggered flows, with each flow consisting of periodic packets originating from […]


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Wi-CBR: Salient-aware Adaptive WiFi Sensing for Cross-domain Behavior Recognition

Kavli Affiliate: Xiang Zhang | First 5 Authors: Ruobei Zhang, Ruobei Zhang, , , | Summary: The challenge in WiFi-based cross-domain Behavior Recognition lies in the significant interference of domain-specific signals on gesture variation. However, previous methods alleviate this interference by mapping the phase from multiple domains into a common feature space. If the Doppler […]


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Electron-magnon coupling at the interface of a “twin-twisted” antiferromagnet

Kavli Affiliate: Jeffrey B. Neaton | First 5 Authors: Yue Sun, Fanhao Meng, Sijia Ke, Kun Xu, Hongrui Zhang | Summary: We identify a "twin-twist" angle in orthorhombic two-dimensional magnets that maximizes interlayer orbital overlap and enables strong interfacial coupling. Focusing on the van der Waals antiferromagnet CrSBr, we show that this twist angle, near […]


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S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamlessly Speech-Text Alignment and Streaming Speech Decoder

Kavli Affiliate: Xiang Zhang | First 5 Authors: Yu Pan, Yuguang Yang, Yanni Hu, Jianhao Ye, Xiang Zhang | Summary: Multilingual speech-to-speech translation (S2ST) aims to directly convert spoken utterances from multiple source languages into fluent and intelligible speech in a target language. Despite recent progress, several critical challenges persist: 1) achieving high-quality and low-latency […]


Continue.. S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamlessly Speech-Text Alignment and Streaming Speech Decoder

S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Streaming Speech Generation

Kavli Affiliate: Xiang Zhang | First 5 Authors: Yu Pan, Yuguang Yang, Yanni Hu, Jianhao Ye, Xiang Zhang | Summary: Multilingual speech-to-speech translation (S2ST) aims to directly convert spoken utterances from multiple source languages into fluent and intelligible speech in a target language. Despite recent progress, several critical challenges persist: 1) achieving high-quality S2ST remains […]


Continue.. S2ST-Omni: An Efficient and Scalable Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Streaming Speech Generation

S2ST-Omni: An Efficient Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Progressive Fine-tuning

Kavli Affiliate: Xiang Zhang | First 5 Authors: Yu Pan, Yu Pan, , , | Summary: Despite recent advances in multilingual speech-to-speech translation (S2ST), several critical challenges persist: 1) achieving high-quality translation remains a major hurdle, and 2) most existing methods heavily rely on large-scale parallel speech corpora, which are costly and difficult to obtain. […]


Continue.. S2ST-Omni: An Efficient Multilingual Speech-to-Speech Translation Framework via Seamless Speech-Text Alignment and Progressive Fine-tuning

Enhancing quantum noise characterization via extra energy levels

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Senrui Chen, Akel Hashim, Noah Goss, Alireza Seif, Irfan Siddiqi | Summary: Noise is a major challenge for building practical quantum computing systems. Precise characterization of quantum noise is crucial for developing effective error mitigation and correction schemes. However, state preparation and measurement (SPAM) errors on many […]


Continue.. Enhancing quantum noise characterization via extra energy levels

Enhancing quantum noise characterization via extra energy levels

Kavli Affiliate: Irfan Siddiqi | First 5 Authors: Senrui Chen, Senrui Chen, , , | Summary: Noise is a major challenge for building practical quantum computing systems. Precise characterization of quantum noise is crucial for developing effective error mitigation and correction schemes. However, state preparation and measurement (SPAM) errors on many current platforms can introduce […]


Continue.. Enhancing quantum noise characterization via extra energy levels