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[2602.16379] Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
[2511.08204] Encoder Fine-tuning with Stochastic Sampling Outperforms Open-weight GPT in Astronomy Knowledge Extraction
arXiv:2511.08204 (cs) View PDF HTML (experimental) Subjects: Computation and Language (cs.CL) Cite as: arXiv:2511.08204 [cs.CL] (or arXiv:2511.08204v1 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2511.08204 Submission history From: Akbar Karimi [ view email] [v1] Tue, 11 Nov 2025 13:08:30 UTC (144 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is...
[2511.07112] More Agents Helps but Adversarial Robustness Gap Persists
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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