Trending research and the full catalog - each paper linked to the benchmarks, methods, and models it introduces.
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25 May 2026
The widespread deployment of generative artificial intelligence (AI) models has raised serious concerns about the proliferation of AI-generated content. This has led to a surge of interest in, and demand for, reliable tracking and detection mechanisms for content that is…
25 May 2026
Physics-informed machine learning (PIML) integrates mechanistic knowledge, typically through partial differential equations (PDEs), into data-driven models. Despite strong empirical performance, its statistical generalisation properties remain poorly understood, especially for…
25 May 2026
The convergence of large language models (LLMs) with 6G networks is fostering a paradigm of autonomous multi-agent cooperation, which in turn is expected to substantially increase east-west traffic.
25 May 2026
Production language-model systems answer a request by partitioning it across an invisible orchestration of worker agents that recompose one integrated report. We ask what this does to a class of defect no single worker can see: a contradiction in the relation between two distant…
24 May 2026
We introduce a user defined probabilistic polygonal representation for plane curves. Given a curve, we select vertices on the curve and connect consecutive vertices by line segments to obtain a polygonal approximation.
23 May 2026
Ethical constraints on open-weight AI models are both a reflection of societal concerns and a foundation for AI governance policy. They are expected to propagate to downstream derivatives while implemented as voluntary metadata disclosures that must be restated at each…
23 May 2026
The rapid expansion of space activities has led to an unprecedented accumulation of technical documentation, operational guidelines, and scientific literature, creating challenges for timely decision-making in space operations.
22 May 2026
Lipid nanoparticles (LNPs) are efficient delivery systems for negatively charged nucleic acids. Their multi-component architecture yields a core-shell structure. Small-angle X-ray scattering (SAXS) is an important characterization technique for LNPs, but recovering internal…
22 May 2026
This paper proposes a multi-layer AI framework for information landscape analysis in the context of information disorder. Rather than treating misinformation detection as a binary fact-checking task, the framework analyzes political and media content across multiple dimensions,…
22 May 2026
Query understanding in large-scale industrial search systems is typically implemented as a cascade of disparate, task-specific components. While individually optimizable, this fragmented architecture incurs high maintenance overhead and results in inconsistent behaviors,…
21 May 2026
Edge deployments of generative inference increasingly face two practical realities: per-device per-model performance is often unknown at deployment time, and it is non-stationary due to user-driven semantic events, background load, and device churn.
Eunsu Kim, Jessica R. Mindel, Kyungjin Kim · 20 May 2026
As large language models (LLMs) increasingly shape how users form, refine, and extend their goals, attributing contributions in human-AI collaboration becomes critical for users calibrating their own reliance and for evaluators assessing AI-assisted work.
19 May 2026
The growing adoption of AI in healthcare, particularly in preventive care, highlights the critical need for accessibility and precision in Medical Question Answering (MedQA).
Yang Liu, Yu-Gang Jiang, YuXuan Li · 18 May 2026
Large Audio Language Models exhibit significant trustworthiness challenges despite performance advances, requiring comprehensive frameworks addressing security vulnerabilities and defensive strategies.
17 May 2026
We apply the Weibull distribution -- a two-parameter family from extreme-value theory -- as a diagnostic framework for element-wise weight magnitude distributions in transformers. At initialization, i.i.d.
Rongrong Ji, Xiawu Zheng, Yongkang Xie · 17 May 2026
Large language models demonstrate significant limitations in abstract reasoning abilities compared to human performance, particularly in complex 3D task understanding, while an automated benchmark pipeline shows that programmatic verification ensures solution uniqueness through cycle consistency.
15 May 2026
How should we make sense of people's interactions with AI companions-conversational systems built for ongoing, emotionally meaningful relationships? First, I argue these interactions should be understood as attachment relationships, since users display all four established…
14 May 2026
In professional sports, a team has clinched the playoffs if they are guaranteed a postseason spot, regardless of the outcomes of any remaining games. As the season progresses, sports fans and other stakeholders are interested in precisely when, and under what conditions, their…
14 May 2026
In this work, we locate and analyze existing undergraduate Artificial Intelligence (AI) programs in the United States in Spring 2026, creating a historic record at a time of great change in this area.
Di Zhang, Kaixuan Fan, Xiang Liu · 12 May 2026
Large language models increasingly need to accumulate and reuse historical information in long-term assistants and agent systems. Simply expanding the context window is costly and often fails to ensure effective context utilization.
12 May 2026
Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capabilities remains unexplored.
Nithin Somasekharan, Rabi Pathak, Manushri Dhanakoti · 12 May 2026
Recent LLM-based agents have closed substantial portions of the scientific discovery loop in software-only machine-learning research, in chemistry, and in biology.
11 May 2026
Automated coaching for oral presentations sits at the intersection of computer-assisted pronunciation training (CAPT), prosody modeling, and speech synthesis, yet no prior work has systematically surveyed and compared existing systems along these dimensions.
Xiaobin Hu, Xinlei Yu, Xiang An · 7 May 2026
4DThinker enables vision-language models to perform dynamic spatial reasoning through 4D latent mental imagery, using scalable data generation and novel fine-tuning methods that outperform existing approaches.