Automated Detection of Multiple Sclerosis Lesions on 7-tesla MRI Using U-net and Transformer-based Segmentation
Compares U-net and Transformer-based segmentation for detecting multiple sclerosis lesions on 7-tesla MRI.
Compares U-net and Transformer-based segmentation for detecting multiple sclerosis lesions on 7-tesla MRI.
CheXOne: Vision-language foundation model for chest X-ray interpretation with explicit reasoning about visual evidence.
Introduces Uni-SafeBench, a safety benchmark for unified multimodal large models testing both understanding and generation capabilities.
Extends scenario approach theory for multi-criteria data-driven decision-making with probabilistic robustness guarantees.
Framework for robot imitation learning using multi-camera view scaling to improve generalization from limited expert demonstrations.
Proposes inverse-free sparse variational Gaussian processes using only matrix multiplications for low-precision parallel hardware.
Studies trade-off between pretraining corpus size and retrieval-augmented generation for language models under fixed data budgets.
CircuitProbe predicts reasoning circuits in Transformers from activation statistics in under 5 minutes, achieving 3-4 orders of magnitude speedup over brute-force methods.
Benchmarks State-Space Models (Mamba) against Transformers and BiLSTM for historical newspaper OCR, addressing quadratic complexity limitations.
CEFR-aligned framework with fuzzy C-means for automated assessment of programming skills in Scratch.
Stochastic Attention inspired by connectome topology provides linear-time expressive attention mechanism.
PG-IPRO algorithm for interactive multi-objective route planning with accessibility preferences.
Study shows multimodal LLMs fail at detecting 3D spatial inconsistencies across multiple views.
Deconfounding scores for causal effect estimation preserve treatment-control distinctions in high dimensions.
PARE framework simulates realistic user interactions for evaluating proactive AI agents and assistants.
Divide-and-conquer approach for scalable matrix mechanisms in differential privacy and synthetic data.
StanceMoE uses mixture-of-experts for actor-level stance detection in geopolitical texts.
Dataset and analysis of autonomous coding agent contributions to real-world GitHub projects over time.
Quantum annealing for VAEs with general Boltzmann priors enables structured latent variable interactions.
MyPhoneBench evaluates privacy compliance of mobile phone-use agents completing benign tasks.
Model-based RL controls focal plane wavefront for exoplanet imaging on extremely large telescopes.
Query-conditioned evidential keyframe sampling for efficient multimodal LLM-based long-form video understanding.
ProOOD method for 3D semantic occupancy prediction handles out-of-distribution inputs and long-tailed class bias.
OptoLlama uses masked diffusion models for inverse design of optical multilayer thin films.
MoA-DepthCLIP adapts CLIP vision-language model for monocular depth estimation with parameter-efficient adapters.
PaperRecon framework evaluates quality and hallucination risks in papers generated by AI coding agents.
RL policy adaptation for robotic manipulation under distribution shift using bounded extremum seeking.
NARCBench for detecting multi-agent collusion using multi-agent interpretability on LLM agent activations.
S0 tuning zero-overhead adaptation of hybrid recurrent-attention models outperforming LoRA on code generation.
Function-based uncertainty quantification for safe learning-based control in safety-critical systems.
Learning to generate mixed quantum states prepared by shallow channel circuits in trivial phases.
RELISH lightweight architecture for text regression with LLMs using iterative latent state refinement.
Survey on Graph Neural Network acceleration techniques across algorithms, systems, and customized hardware.
RobustRAG defense framework with certifiable robustness against retrieval corruption attacks on RAG systems.
Inductive manifold learning approach for nonlinear dimensional reduction with local and global structure.
Domain adaptation with distribution shifts and unobserved confounding using linear structural causal models.
Topological Alignment Spectra method for analyzing multi-scale structural relationships in neural network representations.
Gaussian Process interpretation of wide neural networks with observation noise and arbitrary prior means.
Gradient-based hyperparameter learning via evidence lower bound objective from Bayesian variational methods.
Transformer-based decoder for Varshamov-Tenengolts codes correcting insertion, deletion, and substitution errors.
Multi-armed bandit algorithm using local graph structure to minimize regret under network interference.
Compositional automata learning technique for inferring models of concurrent systems through alphabet refinement.
SetONet neural operator for solving PDEs with variable sensor layouts by treating inputs as unordered sets.
Neural framework for learning conditional optimal transport maps using hypernetworks to generate adaptive transport parameters.
JUSSA framework uses steering vectors to improve LLM-as-a-judge reliability, detecting and mitigating sycophancy through honesty-promoting alternatives.
Binned semiparametric Bayesian networks for efficient kernel density estimation using data binning to reduce computational cost.
Double-Diffusion integrates ODE-prior with denoising diffusion models for spatio-temporal graph forecasting, balancing deterministic and stochastic components.
Klear-Reasoner model with long reasoning capabilities using gradient-preserving clipping policy optimization, with detailed training disclosures.
Knowledge component discovery in programming using representation learning on student code for personalized instruction systems.
Thompson sampling analysis for Sharpe ratio optimization in multi-armed bandit setting, addressing fractional objective with dependent mean-variance.