The Archive

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.

Medical RAG training failure analysis: checker output distribution determines gradient quality; identifies signal collapse and reward hacking.

Neural-symbolic framework for complex query answering over knowledge graphs with multiple free variables.

SafeCtrl-RL: inference-time adaptive safety control for LLM dialogue via RL-driven prompt optimization without retraining.

The nine-year-old startup is replacing hundreds of employees with thousands of AI agents.

68-cell empirical study: LLM agents show +19.69pp higher sensitivity to semantic noise vs. surface noise across reasoning tasks.

Empirical validation of creative quality alignment via chain-of-thought fine-tuning on small models with ~100 expert annotations.

ProAct: proactive agent architecture using idle-time compute to predict and prepare for future user requests via dialogue history analysis.

B³D-RWKV unifies causal RWKV with discrete diffusion via triplet-block layout, achieving O(L) inference with parallel bidirectional decoding.

Gradient-free, training-free watermark for synthetic audio via token vocabulary redundancy, robust to discretization errors.

Large factorial grid study (720 runs) shows optimal learning-rate schedule for sub-100M QAT is invariant across FP16/INT8/INT6 bit-widths.

LECTOR grounds scientific introduction generation via reasoning graphs and structured content to reduce hallucinated citations.

Continual unlearning method for speaker identity in zero-shot TTS, preventing revival of previously unlearned voices under sequential removal.

PolyGnosis 2.0 multi-agent system detects predictive trading signals via Polymarket-GDELT narrative mismatches and harness engineering.

QUIET benchmark for evaluating LLM creative generation (not discriminative ability) via multi-blank cascaded story cloze with objective scoring.

Step-TP: step-level dataset with CoT reasoning for LLM-guided tensor program optimization, enabling composable transformation decisions.