PCdare software registers 3D back surface with biplanar radiographs: application to patients with scoliosis

Optical 3D surface scanning is used increasingly to assess spinal deformity of patients with scoliosis. However, approaches based on optical 3D scanning often underestimate the spinal deformity. To improve the accuracy of such estimates, deeper understanding is required of scoliosis and its effect on the back shape. We present the PCdare research software which registers […]

DiscoverDCP: A Data-Driven Approach for Construction of Disciplined Convex Programs via Symbolic Regression

arXiv:2512.15721v1 Announce Type: cross Abstract: We propose DiscoverDCP, a data-driven framework that integrates symbolic regression with the rule sets of Disciplined Convex Programming (DCP) to perform system identification. By enforcing that all discovered candidate model expressions adhere to DCP composition rules, we ensure that the output expressions are globally convex by construction, circumventing the computationally […]

XTC, A Research Platform for Optimizing AI Workload Operators

arXiv:2512.16512v1 Announce Type: cross Abstract: Achieving high efficiency on AI operators demands precise control over computation and data movement. However, existing scheduling languages are locked into specific compiler ecosystems, preventing fair comparison, reuse, and evaluation across frameworks. No unified interface currently decouples scheduling specification from code generation and measurement. We introduce XTC, a platform that […]

Let the Barbarians In: How AI Can Accelerate Systems Performance Research

arXiv:2512.14806v2 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) is beginning to transform the research process by automating the discovery of new solutions. This shift depends on the availability of reliable verifiers, which AI-driven approaches require to validate candidate solutions. Research focused on improving systems performance is especially well-suited to this paradigm because system performance problems […]

Beyond Blind Spots: Analytic Hints for Mitigating LLM-Based Evaluation Pitfalls

arXiv:2512.16272v1 Announce Type: cross Abstract: Large Language Models are increasingly deployed as judges (LaaJ) in code generation pipelines. While attractive for scalability, LaaJs tend to overlook domain specific issues raising concerns about their reliability in critical evaluation tasks. To better understand these limitations in practice, we examine LaaJ behavior in a concrete industrial use case: […]

GFLAN: Generative Functional Layouts

arXiv:2512.16275v1 Announce Type: cross Abstract: Automated floor plan generation lies at the intersection of combinatorial search, geometric constraint satisfaction, and functional design requirements — a confluence that has historically resisted a unified computational treatment. While recent deep learning approaches have improved the state of the art, they often struggle to capture architectural reasoning: the precedence […]

“I am here for you”: How relational conversational AI appeals to adolescents, especially those who are socially and emotionally vulnerable

arXiv:2512.15117v2 Announce Type: replace-cross Abstract: General-purpose conversational AI chatbots and AI companions increasingly provide young adolescents with emotionally supportive conversations, raising questions about how conversational style shapes anthropomorphism and emotional reliance. In a preregistered online experiment with 284 adolescent-parent dyads, youth aged 11-15 and their parents read two matched transcripts in which a chatbot responded […]

Anubuddhi: A Multi-Agent AI System for Designing and Simulating Quantum Optics Experiments

arXiv:2512.15736v1 Announce Type: new Abstract: We present Anubuddhi, a multi-agent AI system that designs and simulates quantum optics experiments from natural language prompts without requiring specialized programming knowledge. The system composes optical layouts by arranging components from a three-tier toolbox via semantic retrieval, then validates designs through physics simulation with convergent refinement. The architecture combines […]

Spoken DialogSum: An Emotion-Rich Conversational Dataset for Spoken Dialogue Summarization

arXiv:2512.14687v2 Announce Type: replace-cross Abstract: Recent audio language models can follow long conversations. However, research on emotion-aware or spoken dialogue summarization is constrained by the lack of data that links speech, summaries, and paralinguistic cues. We introduce Spoken DialogSum, the first corpus aligning raw conversational audio with factual summaries, emotion-rich summaries, and utterance-level labels for […]

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