· ai
[Paper] Nested Browser-Use Learning for Agentic Information Seeking
Information-seeking (IS) agents have achieved strong performance across a range of wide and deep search tasks, yet their tool use remains largely restricted to ...
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[Paper] Simultaneous Approximation of the Score Function and Its Derivatives by Deep Neural Networks
We present a theory for simultaneous approximation of the score function and its derivatives, enabling the handling of data distributions with low-dimensional s...
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[Paper] AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms
One-to-one tutoring is widely considered the gold standard for personalized education, yet it remains prohibitively expensive to scale. To evaluate whether gene...
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[Paper] BOAD: Discovering Hierarchical Software Engineering Agents via Bandit Optimization
Large language models (LLMs) have shown strong reasoning and coding capabilities, yet they struggle to generalize to real-world software engineering (SWE) probl...
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[Paper] Memorization in 3D Shape Generation: An Empirical Study
Generative models are increasingly used in 3D vision to synthesize novel shapes, yet it remains unclear whether their generation relies on memorizing training s...
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[Paper] Regret-Based Federated Causal Discovery with Unknown Interventions
Most causal discovery methods recover a completed partially directed acyclic graph representing a Markov equivalence class from observational data. Recent work ...
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[Paper] Physics-Informed Neural Networks for Device and Circuit Modeling: A Case Study of NeuroSPICE
We present NeuroSPICE, a physics-informed neural network (PINN) framework for device and circuit simulation. Unlike conventional SPICE, which relies on time-dis...
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[Paper] Le Cam Distortion: A Decision-Theoretic Framework for Robust Transfer Learning
Distribution shift is the defining challenge of real-world machine learning. The dominant paradigm--Unsupervised Domain Adaptation (UDA)--enforces feature invar...
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[Paper] Divergent-Convergent Thinking in Large Language Models for Creative Problem Generation
Large language models (LLMs) have significant potential for generating educational questions and problems, enabling educators to create large-scale learning mat...
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[Paper] RxnBench: A Multimodal Benchmark for Evaluating Large Language Models on Chemical Reaction Understanding from Scientific Literature
The integration of Multimodal Large Language Models (MLLMs) into chemistry promises to revolutionize scientific discovery, yet their ability to comprehend the d...
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10 AI terms that will help you look like you're not completely lost
The Fast‑Moving World of AI and Why You Need to Keep Up In just over a decade we’ve gone from talking about AI as a science‑fiction concept—something only Sara...
- · ai
[Paper] CubeBench: Diagnosing Interactive, Long-Horizon Spatial Reasoning Under Partial Observations
Large Language Model (LLM) agents, while proficient in the digital realm, face a significant gap in physical-world deployment due to the challenge of forming an...