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DITL framework applies dataset-difficulty signals to mammography transfer learning, targeting clinical-scale breast cancer screening.
VetClaw is an edge-cloud agentic system for veterinary disease screening combining camera sensors, VLMs, and LangGraph-based workflow orchestration.
Desktop-Delta Bench isolates whether computer-use agents understand GUI state transitions caused by actions, beyond end-task success metrics.
Reinformed Dreamer applies asymmetric RL with latent guidance to improve world model training and policy learning under partial observability.
Federated learning approach for time-to-event modeling in distributed system failure prediction without centralizing sensitive operational data.
Framed behavioral experiment shows competitive AI race dynamics incentivize riskier development, validating speed-safety trade-off under falling-behind pressure.
CHARM is a multimodal graph foundation model enabling zero-shot transfer via hierarchical context modeling on text-image-augmented graphs.
UniMem hybrid episodic-parametric memory for LLM agents resolves stability-plasticity dilemma across boundary-agnostic evolving task streams.
MDTransformer uses mode-division photonic hardware with inverse-designed crossbars to accelerate Transformer inference with reduced phase-shifter overhead.
Study finds instruction-tuned LLMs exhibit stronger syntactic convergence to human dialogue patterns than humans themselves across diverse grammatical constructions.
Pictura enables perspective-view self-play for autonomous driving policies without privileged state, bridging simulation-to-deployment gap using egocentric camera observations.
Parallel Decoding Distillation accelerates video/image diffusion models via trajectory-based training, avoiding mode collapse and motion loss of score distillation approaches.
Analysis of Sharpness-Aware Minimization and Muon optimizer investigates matrix-aware geometry for robust generalization under parameter perturbations.
Empirical evaluation of nine Tabular Foundation Models reveals robustness gaps under distribution shift versus ensemble tree methods across diverse pre-training strategies.
Study shows LLM-generated Kubernetes security patches improve when prompted with runtime service topology context rather than isolated KSPM findings.
MemLens provides value-aware memory management for LLM agents with interactive analytics, treating memory records as first-class objects to reduce redundancy.
Framework formalizes co-drift failure prediction in self-driving networks by treating monitoring, analytics, and actuation as coupled macro-intents.
GARI introduces representation-level soft-equivariance design for generic sequence backbones using aligned generator views across modalities.
Deep RL for quadcopter control via physics-aware end-to-end learning with high-fidelity actuator dynamics simulation.
GARFIELD: probabilistic latent model for predicting distributions over future scene kinematics from partial observations.
OpenAI field report documents how AI coding agents accelerate scientific computing workflows in genomics and adjacent domains.
RL for code optimization via learnable execution time rewards and DMC-Optim framework to overcome measurement noise and sparsity.
Quasi-SVD: GPU-parallelized differentiable matrix factorization with Lie-constrained orthogonality for real-time medical imaging.
PRISM-AH: multimodal framework for detecting ambivalence/hesitancy in health behavior video via cross-modal conflict reasoning.
Kontra: taxonomy and detection framework for cross-modal knowledge inconsistencies in Wikipedia, Wikidata text/tables/KGs.
Solver-guided LLM framework for instance-wise operations research formulation selection in multi-warehouse inventory allocation.
Polistemics: theory-grounded benchmark for evaluating LLMs as political information mediators via epistemic modesty standard.
MODUS: decoder-only any-to-any multimodal model supporting arbitrary modality combinations with pre-trained model priors.
ClinPRISM: cost-effective multimodal LLM for QA over irregular clinical time series via sparsity-aware encoding.