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We present a retrieval-augmented translation pipeline tailored to low-resource technical Korean corpora. The method improves terminology consistency and reduces factual drift in domain-heavy documents.
PDF 열기This paper introduces sparse routing across expert groups for efficient long-context reasoning. We show lower inference cost while preserving performance on multi-document QA benchmarks.
PDF 열기We build a benchmark for evaluating trust calibration when multiple AI agents collaborate on scientific writing tasks. Results show confidence estimates remain poorly aligned under disagreement.
PDF 열기GraphDiffusion combines graph neural operators with diffusion priors to improve uncertainty estimates in molecular property prediction. The approach outperforms deterministic baselines on OOD compounds.
PDF 열기We propose an adaptive curriculum that reorders multimodal training data according to evolving confidence and disagreement signals. The strategy significantly stabilizes vision-language alignment with noisy web...
PDF 열기This work studies request-aware scheduling for heterogeneous edge TPU clusters. By combining queueing features and model cost profiles, we reduce p95 latency across bursty workloads.
PDF 열기OpenDataset-30K provides a cleaned and documented corpus for paper-level and section-level summarization. We detail filtering heuristics and release train-dev-test splits with quality annotations.
PDF 열기We introduce a layout-aware transformer architecture for parsing noisy PDF documents and recovering semantic structure. The model improves extraction quality on math-heavy articles and scanned proceedings.
PDF 열기Counterfactual regularization is used to constrain temporal causal graph discovery from observational sequences. We report stronger edge precision in partially observed healthcare data.
PDF 열기This paper proposes a privacy-preserving Bayesian optimization framework for site-distributed clinical trial tuning. The federated method improves sample efficiency while protecting participant-level data.
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