This work proposes RENSA, a federated SPARQL query generation framework that leverages an extension of SPARQL Builder Metadata (SBM), and demonstrates that RENSA infers class and authority constraints for query variables, enabling the identification of data sources even across heterogeneous endpoints.
Victor Eiti Yamamoto, Hideaki Takeda, Yasunori Yamamoto· 0 citations
Using human ideas as the AARs' initial research direction does not improve performance, suggesting current AARs may not need guidance from experienced researchers, and suggests that automating alignment research on well-characterized failures may be practical in the near term.
Yueh-Han Chen, Jia-Xin Wen, J. Kirchner· 0 citations
The results support frozen verification as a training signal for evidence selection, while showing that strict boundary precision remains comparatively weaker.
Mingwen Zhang, Jisheng Dang, Minqiang Yang et al.· 0 citations
Personality-narrative conditioning beat demographic-only conditioning, but neither surpassed simple real-data baselines; Synthetic panels are thus not survey substitutes; their value is diagnostic, with operational use confined to settings lacking real data.
Howard Kim, Keun Tae Cho· 0 citations
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Cross-jurisdiction regulatory divergence detection is introduced: given an FDA requirement and an EMA requirement on the same topic, classify their relationship as AGREE, DIVERGE, or SILENT and three directional observations emerge at pilot scale.
Chu-Chu Wu, Zhi-Ying Zhou, Jing-Zhu Hu et al.· 2 citations
By using VAD-derived segment boundaries, the algorithm stabilizes Whisper's text conditioning, allowing us to safely maintain continuous historical context across batched audio segments, all while maintaining high-throughput inference speeds.
Cross-dataset analysis shows that semantic chunking improves extraction datasets with explicit relation cues, such as GM-CIHT and DDI, while fixed chunking remains competitive or stronger for dense biochemical extraction and binary classification settings such as ChemProt and ADE.
Riya Ahuja, Tim Kacprowski, Roya Shiasi Sardoabi Institute of Data Science in Biomedicine et al.· 0 citations
DIASENTINEL demonstrates a practical framework for reliable, auditable, and privacy-preserving LLM-based clinical decision support for type 2 diabetes mellitus risk screening and guideline-grounded report generation from electronic health records (EHRs).
This work introduces PaperGym, a unified framework that turns each research paper into a complete training environment, and releases the pipeline, the 20,000-instance corpus PaperGym-20k, and the benchmarks PaperGym-Innov and PaperGym-Design.
Yu-Han Wang, Zhengxi Lu, Yuchen Yan et al.· 0 citations
This work introduces ASPIRE, a benchmark for vague-goal-driven self-evolution and shows that vague goals redirect search effort toward goal interpretation, and evaluates the resulting systems on a hidden, expert-authored set of 520 items spanning six goals.
Yu-Hao Wu, Jingyuan Zhang, Jia-Jun Shi et al.· 0 citations
These findings show that recognizing successful actions is insufficient; agents must also transform feedback into executable and transferable policies, and provide a unified framework for diagnosing this process and identifying the bottlenecks that prevent agents from translating interaction experience into reliable self-improvement.
Jia-Jun Shi, Siyang Tao, Yu-Hao Wu et al.· 0 citations
Results show that first-token clues can guide multi-token concept recovery, while subsequent hidden states provide vectors for readout and intervention.
A new method, called CW-Net, translates the reasoning process of an autonomous vehicle’s AI system into understandable concepts that explain its behavior.
MIT News · Artificial Intelligence· news.mit.eduAug 31, 2026
With millions of users across the world, Julia has been used to conduct cutting-edge research and to design new drugs, jet engines, heat pumps, and more.
A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.
New MIT research could lead to better materials for a fossil-fuel-free process for making the chemical that's essential to fertilizer and other products.
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