Political discourse is widely perceived to be growing more hostile, yet robust evidence remains scarce. This study examines blame attribution in the Danish Parliament from 1997 to 2026, combining a purpose-built classifier, BlameBERT (F1: 0.80), with multilevel statistical modeling. The classifier is constructed using...
Markus Lundsfryd Jensen, Rune Egeskov Trust, Kenneth C. Enevoldsen et al.· 0 citations
Argument Mining (AM) transforms natural language into its underlying argument structures. This transformation is typically realized through a sequence of AM tasks that form an end-to-end AM pipeline. However, AM approaches often differ in how they conceptualize these tasks, making direct comparisons between them diffic...
Siddharth Bhargava, Sara Tonelli, Patricia Martín-Rodilla· 0 citations
This work presents the task and results of the CHiME-9 challenge for Enhancing Conversations to address Hearing Impairment. The challenge considers the scenario of four-party conversations in a noisy, cafeteria-style environment with interfering speech sources and sound effects. Participants are provided with audio rec...
Robert Sutherland, Thomas Kuebert, Marko Lugger et al.· 0 citations
PACE-dLLM is proposed, which fits this parametric cliff in closed form at each step, sets the next horizon by its saturation point, and uses an independent confidence threshold for token commitment, and achieves the best average accuracy on both open-source dLLM backbones.
Xiao-Cheng Lu, Shu-Han Guo, Zi-Yue Ma et al.· 1 citation
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Vision-language models (VLMs) are increasingly used to interpret charts and generate natural-language explanations for socially consequential data. However, they may produce different narratives for the same chart when only the referenced social group changes, reinforcing stereotypes and misleading decisions. Despite t...
Mizanur Rahman, Huan Wu, Arash Asgari et al.· 0 citations
A structured multi stage interface generation framework that decomposes the task into visualization design representation, generation of multiple interface candidates, constraint-aware critique, and self-refinement is proposed, demonstrating a practical path toward more reliable language-driven interactive visualizatio...
Multimodal embedding models are deployed at scale: retrieval indices, benchmark results, and behavioral audits all depend on the base model's exact outputs. Extending such a model to a new modality with existing parameter-efficient methods silently changes those outputs; LoRA-style adaptation rewrites the text path whe...
Abdul Basit Tonmoy, Kazi Fardinul Hoque, Md. Shahrier Islam Arham et al.· 0 citations
The Differentiable Fuzzy Inference Layer (DFIL), a dual-path prediction head pairing a standard classifier with a scalar-bottlenecked branch grounded in a bank of ordered membership functions, is introduced.
The SpecialEduBench, which measures pedagogical competence along knowledge, skill, and attitude, is introduced, with 4,537 knowledge items and with 200 skill items and 68 attitude items built on recorded intervention, the attitude items crossing pressure with monitoring into 192 response cells.
Ji-Hoi Na, Taeyeon Kim, Sun-Ga Kong et al.· 0 citations
Across three multi-hop QA benchmarks, with the evaluation protocol fixed before the full-scale run, the CoVeR-gated agent matches the answer accuracy of both the full-budget agent and the always-verify baseline within a fraction of an EM point.
This work test whether expressed uncertainty, provenance-aware assertion, and explicit belief revision can be implemented as a behavior layer over a fixed language model over a fixed language model and supported conclusions are limited to the by-construction audit guarantee, store-dependent partial correction discrimin...
This study provides a compact and scalable semantic foundation for large-scale information processing and evidence mapping in water treatment research by developing WaterBERT, a domain-adapted encoder model designed for semantic representation and structured information extraction from water treatment texts.
Mu-Di Zhai, Rui-Hong Qiu, Qing-Yun Zeng et al.· 0 citations
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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