Papers with CVSS
AutoCVSS: Assessing the Performance of LLMs for Automated Software Vulnerability Scoring (2025.emnlp-industry)
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| Challenge: | Increasing number of daily disclosed software vulnerabilities imposes significant pressure on security analysts, extending the time between disclosure and exploitation. |
| Approach: | They propose to use Large Language Models to automate vulnerability risk score prediction using the industrial CVSS standard. |
| Outcome: | The proposed model complements baselines in data-scarce settings without annotated data, highlighting their value in improving vulnerability management. |
StreamSpeech: Simultaneous Speech-to-Speech Translation with Multi-task Learning (2024.acl-long)
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| Challenge: | Existing simultaneous translation methods focus on text-to-text and speech-totext translation. |
| Approach: | They propose a Simul-S2ST model that jointly learns translation and simultaneous policy in a unified framework of multi-task learning. |
| Outcome: | The proposed model can perform offline and simultaneous speech recognition, speech translation and speech synthesis via an "All-in-One" seamless model. |
CVSS Corpus and Massively Multilingual Speech-to-Speech Translation (2022.lrec-1)
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| Challenge: | Existing work on speech-to-speech translation (S2ST) systems rely on text representation, but they are text-centric. |
| Approach: | They introduce a massively multilingual-to-English speech-tospeech translation corpus . they synthesize the translation text from the Common Voice speech corpus and CoVoST 2 into English . |
| Outcome: | The proposed corpus outperforms existing models on CoVoST 2 by 5.8 BLEU . the proposed model outperformed the previous state-of-the-art model without extra data . |
S2ST-Omni: Hierarchical Language-Aware SpeechLLM Adaptation for Multilingual Speech-to-Speech Translation (2026.findings-acl)
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| Challenge: | S2ST-Omni integrates a speech-to-text frontend with a modular, plug-and-play text-tospeech backend. |
| Approach: | They propose a compositional S2ST framework that integrates a speech-to-text frontend with a modular, plug-and-play text-tospeech backend. |
| Outcome: | The proposed framework outperforms existing frameworks in translation and synthesis . it integrates a speech-to-text translation frontend with a plug-and-play text-tospeech backend . |