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Conditional kernel ridge regression with unpenalized features via conditionally positive definite kernels; primarily theoretical ML contribution.
Paris 2.0: first decentralized video generation model trained without GPU clusters, extending prior Paris 1.0 image work.
llama.cpp adds fast Walsh-Hadamard transform (FWHT) for CUDA, yielding 1–2% prompt-processing and 7–9% token-generation speedups with quantized KV-cache.
Neuronal Stochastic Attention Circuit for uncertainty in continuous-time representation learning using C.elegans-inspired circuits.
Neural operator surrogates for Bayesian inverse design in CFD to accelerate MCMC sampling for aerodynamic geometry inference.
Retrying vs resampling in AI control: retrying leaks exploitable monitor rationale; resampling preserves safety without information leakage.
Chris Olah comments on papal encyclical; off-topic for AI industry professionals unless directly addressing AI ethics.
Multi-objective textual gradient optimization for LLM judges: gradient conflicts cause failure modes; six decomposition modes tested.
Uncertainty quantification for activation oracles interpreting LLM internals; bootstrap frequency is best-calibrated confidence method.
L2IR: graph fraud detection combining GNNs and LLMs to infer fraudster intent behind suspicious connections.
DRScaffold: training lightweight vision-language models for dense-scene reasoning with explicit grounding between inference steps.
Transformer paper co-author argues for moving beyond transformer architecture; Pathway's post-transformer research gaining attention from technical community.
Peak-then-collapse failure in GRPO tool-use training on knowledge graphs: four recurring failure modes shift rather than resolve.
CityRep benchmark evaluates urban representation learning across cities and modalities using spatially-structured splits to prevent data leakage.
MLP-LDRU architecture improves length generalization in neural networks via log-depth recurrent units with associativity-biased operators.
SKILD unifies image generation and super-resolution via scale-invariant diffusion in K-space, leveraging scale invariance in natural and physical systems.
CausaLab environment benchmarks LLM agents on interactive causal discovery with validation of both solutions and underlying causal mechanisms.
Boston Dynamics and Hyundai plan to train Atlas humanoid robot using football video learning, releasing progress via 'School of Football' documentary series.
3D foundation model for light sheet fluorescence microscopy enables few-shot segmentation and classification of volumetric biological imaging data.
RAG framework detects potentially abusive clauses in Chilean Terms of Service using retrieval-augmented generation for legal document analysis.
STORM internalizes spatial-temporal reasoning in video-language models via implicit visual memory instead of externalizing to textual chain-of-thought.
AdvantageFlow applies advantage-weighted RL to forward-process diffusion optimization in Stable Diffusion, outperforming reverse-process baselines.
Orthogonal bottleneck representation prior constrains RL encoder features to low-dimensional subspaces without auxiliary objectives or pretraining.
NeoBERT evaluated on dementia detection from Filipino-English code-switched speech, first systematic study in this low-resource clinical NLP setting.
MAGIC: training-free coreset selection for vision-language model instruction tuning via multimodal alignment signals.
Framework for systematizing GenAI evaluation concepts (reasoning, fairness, creativity) into measurable definitions using AI assistance.
Statistical inference methodology for SGD trajectories in infinite-variance regimes via weak convergence theory.
Causal inference methods for LLM development decisions: data mixtures, reward models, routing, and evaluation.
Deployment-complete benchmarking: framework ensuring benchmark evidence resolves deployment decisions via conformal coverage.
Fuzzy PyTorch: framework for evaluating numerical variability in deep learning via stochastic arithmetic integration.