Research
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Curated daily papers, lab research blogs and national AI research programs across the US, China, EU, UK, Japan and beyond.
Latest in Research
30 storiesXMSE-Aware Adaptive Empirical Bayes Estimation
Empirical Bayes (EB) estimators can match the first-order asymptotic risk of maximum likelihood (ML) while behaving very differently at second order: recent exc…
Enabling self-supervised learned primal dual with Noise2Inverse
X-ray computed tomography reconstruction is an ill-posed inverse problem, particularly in low-dose and sparse-angle settings where measurements are noisy and in…
Parametric Open Source Games
Open-source game theory studies agents whose behavior may depend on one another's decision procedures, but most existing models use discrete or symbolic program…
Towards Explainable Adjudicative Variance: Quantifying Judicial Discretion via Gated Multi-Task Learning
Legal outcome prediction must disentangle objective case facts from adjudicative context. Merit-based rulings rely on factual evidence while technical disposals…
SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision
Mesh subdivision is a fundamental operation for converting coarse, editable meshes into high-resolution surfaces, with broad applications in digital asset creat…
Kolmogorov Arnold networks (KAN) for aerodynamic prediction: a comparison with MLPs and GNNs
Kolmogorov Arnold networks (KAN) have recently been introduced as a (deep) neural network architecture whose trainable parameters adapt the activation functions…
fTNN: a tensor neural network for fractional PDEs
We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking the fracti…
Safe Autoregressive Image Generation with Iterative Self-Improving Codebooks
Unlike diffusion-based models that operate in continuous latent spaces, autoregressive unified multimodal models produce images by sequentially predicting discr…
OpenRCA 2.0: From Outcome Labels to Causal Process Supervision
Root cause analysis (RCA) poses a holistic test of LLM agentic capabilities, such as long-context understanding, multi-step reasoning, and tool use. However, ex…
A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO
We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacing the un…
Ask, Don't Judge: Binary Questions for Interpretable LLM Evaluation and Self-Improvement
Evaluating LLM outputs remains a major bottleneck in NLP: human evaluation is expensive and slow, lexical metrics correlate poorly with human judgments on open-…
Compositionality and the lexicon in evolutionary semantics
Formal semantics has shown that sentence meanings arise by recursively composing lexical meanings, yet much of the literature on semantic universals models eith…
How Good Can Linear Models Be for Time-Series Forecasting?
Time-series forecasting research has been moving steadily toward larger architectures, from specialized transformers to general-purpose foundation models, on th…
Recovering Governing Equations from Solution Data: Identifiability Bounds for Linear and Nonlinear ODEs
Learning governing equations from observed solution data is a fundamental challenge in scientific machine learning \cite{bruntonDiscoveringGoverningEquations201…
Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search
Job-search platforms rely on low-bandwidth query interfaces that often fail to capture the high-dimensional complexity of candidate profiles. We present an end-…
A Multi-Fidelity Convolutional Autoencoder-Transfer Learning Framework for Guided-Wave-Based Damage Diagnosis Using Large Simulated and Limited Experimental Datasets
Guided wave-based structural health monitoring (GWSHM) with onboard transducers offers significant potential for the early diagnosis of damage in engineering st…
Multilingual Reasoning Cascades Need More Context
Translation cascades for reasoning translate the query from another language to English, reason in English, and translate the answer back to the original langua…
LLM-Based Examination of Eligibility Criteria from Securities Prospectuses at the German Central Bank
Verifying the eligibility of securities as collateral is a key responsibility of the German Central Bank. However, manually verifying these assets against legal…
Autoregressive Boltzmann Generators
Efficient sampling of molecular systems at thermodynamic equilibrium is a hallmark challenge in statistical physics. This challenge has driven the development o…
Understanding the brain with AI-driven explanations and experiments
Researchers introduce generative causal testing, which translates black box models into clear hypotheses and verifies them in the scanner, revealing what specif…
Multilingual Hematology Visual Question Answering Dataset
Vision Language Models (VLMs) have shown promising capabilities in medical image analysis by jointly understanding visual and textual information for tasks such…
FUTO Swipe: Layout-Agnostic Neural Swipe Decoding
Neural swipe decoders are typically tied to the keyboard they were trained on, requiring a new corpus and training run for each layout. In this report, we docum…
Automatic Generation of Highlights for Academic Paper Via Prompt-based Learning
Highlights provide a concise summary of the main contributions of an academic paper and help readers quickly understand its focus. However, many journals do not…
Pre-Warm: Input-Conditioned Weight Initialization for Convolutional Neural Networks
We introduce Pre-Warm, a simple yet effective zero-training-cost method for data-conditioned initialization of the first convolutional layer. Before the first f…
UC-Search: Risk-Aware Test-Time Search for Delayed Constrained Time-Series Control
Time-series models are usually scored as forecasters, yet deployed systems often require delayed decisions under uncertainty and hard feasibility constraints. U…
Physics Question Scene Graph: Fine-grained Evaluation of Physical Plausibility in Text-to-Video Generation
Video generation models are increasingly capable of producing realistic videos, but they still struggle to generate videos that follow basic physical laws. Comp…
REViT: Roto-reflection Equivariant Convolutional Vision Transformer
In this paper, we propose a discrete roto-reflection group equivariant vision transformer with convolutional attention. Roto-reflection equivariant networks pre…
Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities
Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Information Scie…
Efficient Remote Sensing Instance Segmentation with Linear-Time State Space Distilled Visual Foundation Models
The computational complexity of Transformers scales quadratically with the number of tokens, which significantly constrains the efficiency of vision models, par…
Stagnant Neuron: Towards Understanding the Plasticity Loss in Multi-Agent Reinforcement Learning Value Factorization Methods
Multi-Agent Reinforcement Learning (MARL) value factorization methods can suffer from a loss of plasticity, gradually failing to adapt when transferring to new …