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This paper introduces a hybrid quantum-inspired Kolmogorov-Arnold network for privacy-aware federated learning of ECG data, demonstrating reduced parameters and communication costs while improving classification metrics compared to traditional MLP.
This paper presents a retrospective analysis of the CODS 2025 AssetOpsBench Challenge, examining leaderboard saturation, hidden evaluation effects, and design patterns rewarded.
This paper introduces the one-sided conversation problem (1SC), addressing how to reconstruct missing dialogue and generate summaries when only one speaker's turns are available in real-world settings like telemedicine and call centers. The authors evaluate prompting and finetuned models on multiple datasets, finding that access to future context and utterance length information improves reconstruction, while high-quality summaries can be generated without full dialogue reconstruction.