We introduce the Illinois Social Attitudes Aggregate Corpus (ISAAC), an open, modular, and accessible corpus of 527 million+ English-language Reddit posts selected for relevance to six key social group distinctions based on race, sexuality, age, ability, body weight, and skin tone, covering the 17-year period from 2007...
Babak Hemmatian, Sarah Hadjarab, Jessica Chen et al.· 0 citations
LEGO is proposed, a dual-module framework that synergizes Legal Expert GraphRAG and expert Chain-of-thought for complex legal reasoning that achieves the best results among the evaluated baselines on the open-ended benchmarks.
Qing-Jing Chen, Jun-Kai Zhang, Shao-Chun Wang et al.· 0 citations
Under this setup, learned planning is a weak relevance signal rather than a replacement for strong retrieval, and packing-order and score-flatness analyses did not identify a stable mechanism.
A sentence-level benchmark for evaluating the ability of LLMs to classify interpretive canons as articulated by Larenz in the tradition of Savigny is contributed, operationalizing this conception of interpretation as classification criteria.
Felix Ringe· 0 citations
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Current literature evaluates large language models (LLMs) on multilingual kinship understanding using multiple choice benchmarks, treating it as a recognition problem. We instead prompt five open weight LLMs to generate kinship terms in three non Western languages (Hindi, Tamil, and Korean) across two communicative tas...
No single Large Language Model (LLM) is uniformly reliable across queries, motivating multi-model inference systems that either route among models or combine their outputs. However, routing stops after selecting an initial model, while dense collaboration invokes peers on every query. We show that collaboration is non-...
Norah Alballa, Wen-Xuan Zhang, Salma Kharrat et al.· 0 citations
PHONOS is a streaming module for real-time SA that performs accent neutralization in a privacy sense: reducing accent-origin cues by converting non-native segmental realizations toward a chosen target accent domain.
Probability-floor samplers substantially narrow the blind spot, demonstrating that the choice of truncation criterion matters for retaining human-used tokens and motivate decoding methods that preserve contextually appropriate low-probability choices while maintaining generation quality.
E. Arias, Nurzhan Sapargali, Christian Heumann et al.· arXiv.org· 2 citations
VMMU, a Vietnamese Multitask Multimodal Understanding and Reasoning Benchmark, is introduced to evaluate how vision-language models (VLMs) interpret and reason over visual and textual information beyond English, showing that the primary source of failure is not OCR, but instead multimodal grounding and reasoning over t...
V. Dang, A. Vo, Emilio Villa-Cueva et al.· 0 citations
This paper applies various NLP techniques to demonstrate feature de-biasing, feature compression, and industry classification in the commercial insurance context to show that NLP is not merely a supplementary tool but a foundational element of modern, data-driven insurance analytics.
Pan-Yi Dong, Z. Quan· North American Actuarial Jou...· 2 citations
It is proved that coherence optimization is equivalent to description-length regularization, and that among all such regularization schemes, coherence regularization with a prior derived from a pretrained model optimizes a lower bound of worst-case accuracy for semi-supervised learning.
Tianyi Alex Qiu, A. Ismail, Zhonghao He et al.· Trans. Mach. Learn. Res.· 1 citation
A ModernBERT Bi-Encoder model is developed that achieves 98.4% accuracy on the PAN21 authorship verification task and identifies loss function, batch size, training duration, pre-trained model, input context length, and random text span data augmentation as important factors of model performance.
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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