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 storiesA probabilistic framework for online test-time adaptation
This paper presents a probabilistic framework for online test-time adaptation problems. In them, a model is trained on labeled data but must adapt to unlabeled …
Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data
This paper addresses model-free continuous-time mean-field control in a setting where the population dynamics evolve continuously according to an unknown McKean…
SocialPersona: Benchmarking Personalized Profiling and Response with Multimodal Social-Media Context
Personalized language-model assistants are often evaluated through a memory lens: can a model recall preferences users have explicitly stated in dialogue? More …
Scientific discovery as meta-optimization: a combinatorial optimization case study
Scientific discovery is fundamentally an optimization problem, defined by a vast "state space" of theories and experiments, and an evaluation criterion based on…
Reasoning Quality Emerges Early: Data Curation for Reasoning Models
Supervised fine-tuning (SFT) on a small, high-quality set of long reasoning traces is an effective approach for eliciting strong reasoning capabilities in Large…
SatSplatDiff: Geometry-preserving generative refinement for high-fidelity satellite Gaussian Splatting
Gaussian Splatting has been recently explored for satellite 3D reconstruction, demonstrating flexibility and efficiency in representing radiometrically diverse …
Training Observable Control Policies to Expose Agent State Through Actions
Physical or operational constraints often impose communications limitations on autonomous agents. Such limitations complicate monitoring or multiagent coordinat…
From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond
The AI community has framed the relationship between large language models (LLMs) and world models as a dichotomy: LLMs predict tokens; world models simulate re…
Artifacts 22: Zyphra, Cohere, and Poolside are expanding the breadth of the ecosystem
An assessment of the open ecosystem and the motivations behind releasing models…
Large Language Model-Assisted Cleaning of Report-Derived Labels in a Large-Scale Chest CT Dataset
Purpose: To evaluate whether large language model (LLM)-assisted label cleaning can identify label-report discordance in CT-RATE, a large-scale public chest CT …
Not All Claims Are Equally Risky: FACTOR for Adaptive Verification in Factual Long-Form Generation
Large Language Models (LLMs) generate fluent long-form text, however, often add unsupported factual claims. Existing verification techniques improve factuality …
ROMEVA: Geometry-Preserving Vocabulary Expansion for Roman Urdu Language Models
Multilingual Language Models like mBERT are widely used for low-resource NLP, yet their adaptation to morphologically inconsistent languages such as Roman Urdu …
FetSelect: Task-Specific Architectures and Self-Supervised Learning for Automated Fetal Ultrasound Frame Selection
Automated frame selection for fetal biometry remains under addressed, with most prior work targeting generic quality assessment or downstream measurement pipeli…
Generative Relightable Avatars
We present Generative Relightable Avatars (GRA), a person-specific method for photorealistic free-view rendering and environment-map relighting of full-body hum…
Joint Air Traffic Flow and Capacity Management via Answer Set Programming
Operational Air Traffic Flow and Capacity Management (ATFCM) balances flight demand with available sector capacity, to ensure safe and efficient operations. Mat…
AdaReP:Adaptive Re-Planning under Model Mismatch for Neural World-Model Predictive Control
Neural world models coupled with model predictive control (MPC) replan at every environment step to bound accumulated prediction error, but this incurs substant…
A Matter of Time: Towards a General Theory of Agency
Agency is often invoked in research on philosophy, biology, and cognitive science without a clear account of how it originates from material organization. Build…
Automated Semantic Fault Localization in SysML v2: A Human-in-the-Loop Framework Using Knowledge-Graph Augmented LLMs
SysML v2's textual syntax enables compiler-based validation of model structure and language conformance. However, semantic mistakes that preserve syntactic vali…
Leveraging Similarities in Multi-Armed Bandits
In many online learning and bandit problems, the actions we consider possess inherent similarities--for instance because they share latent traits, tags, or hier…
Selective Time Series Forecasting via Metalearning
Deep learning methods have achieved state-of-the-art in time series forecasting, yet their accuracy varies considerably across samples, as some instances remain…
SPIRAL: Learning to Search and Aggregate
Language model reasoning can be substantially improved at test time via scaffolds that scale inference compute across different primitives -- sequential reasoni…
Sentence-Level Contextual Entrainment in Large Language Models
Contextual entrainment, which is a newly discovered phenomenon in large language models (LLMs), refers to the tendency of a model to assign higher probabilities…
Flood Mapping from RGB imagery using a Vision Foundation Model
Timely, high-resolution maps of flood extent around settlements are essential for emergency response and damage assessment. We consider airborne RGB imagery for…
A Dual Edge Spatial Jacobian Image Graph for Interpretable Diabetic Retinopathy Grading
Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requires more …
EERLoss: A Novel Loss Function for Training Deep Biometric Models. A Case Study in Keystroke Dynamics
Deep learning approaches to biometric verification are commonly trained by optimizing indirect objectives, creating a misalignment between the optimization proc…
Cost-Optimal Decision Diagrams for Stochastic Boolean Function Evaluation
In many decision-making scenarios, acquiring information incurs different costs. We consider the problem of constructing a deterministic evaluation strategy tha…
OrbitForge: Text-to-3D Scene Generation via Reconstruction-Anchored Video Synthesis
Generic text-to-video models can be used as rich open-world scene priors. Despite the high quality of today's generated videos, they do not directly yield relia…
Real vs. Complex Spectral Bases for Neural Operators: The Role of Green's Function Alignment
Fourier Neural Operators (FNO) learn solution operators of partial differential equations by parameterizing global convolutions in the complex Fourier domain. F…
Cage-based Texture Transfer with Geometric Filtering
Real-time texture transfer expands the creative horizon for interactive applications, enabling seamless detail projection in scenarios that range from digital c…
MJEPA: A Simple and Scalable Joint-Embedding Predictive Architecture for Audio-Visual Learning
Self-supervised learning from large-scale video data has emerged as a dominant paradigm for visual representation learning. Since audio and visual streams natur…