The Archive

Musk texted OpenAI's president and co-founder saying that he and CEO Sam Altman "will be the most hated men in America."

FunFuzz evolutionary fuzzing framework uses LLMs with multi-island search and feedback-driven prompt adaptation for structured input generation.

Static analysis framework for recursive SHACL shape definitions to decide constraint document implication.

Benchmark reveals audio-language models fail to leverage clinical context for dysarthric speech recognition despite multimodal capacity.

Conditional VAE with latent mixture scheduling enables fine-grained topological control in graph generation for drug discovery.

Decoupled diffusion planner using cost-conditioned generation and reward gradients for offline safe RL with dynamic cost limits.

Lindeberg principle derives Wasserstein distance bounds between infinite-width deep networks and Gaussian limits.

Reddit user reports Claude generates excessive detail and meta-commentary in outputs, seeks prompt engineering workarounds.

TOC-SR framework compresses diffusion models to one-step super-resolution via architecture search and generative distillation.

U-Define studies interaction workflows for applying hard and soft constraints in LLM-based planning systems.

Both Anthropic and OpenAI have partnered with asset managers to more aggressively market their enterprise AI products.

Multi-agent LM interactions exhibit misalignment contagion where anti-social behavior spreads across models in sequential gameplay.

Simon Willison built an interactive browser playground for testing Redis's proposed array data type and new AR* commands via WASM.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Two of the most powerful people in AI—Sam Altman and Elon Musk—began their face-off in court in Oakland, California, last week. Musk is suing OpenAI, alleging that the millions he spent to…

Synthetic PET imaging from CT scans via deep learning for improved lung cancer histological subtype classification.

Bolek: compact multimodal LLM grounding molecular reasoning in fingerprint embeddings for drug discovery explainability.

Developer built real-time multiplayer .io game Node Control using Claude 4.6 and 4.7, now live at nodecontrol.gg with multi-region deployment.

Triple spectral fusion framework for IMU-based human activity recognition using adaptive filtering and temporal context correlation.

Deep learning method for motion in-betweening in 3D animation that aligns with professional animation workflows rather than academic assumptions.

Systematic audit reveals AI-generated code exhibits distinct machine-signature defects and reasoning-complexity trade-off in maintainability.

ReClaim: generative transformer trained on 43.8B medical events from MarketScan claims data for healthcare foundation model development.

Scalable framework using foundation vision models to detect rooftop solar panels from satellite imagery for city-level solar power profiling.

Analysis identifies latent reasoning suppression in multimodal models where visual tokens are semantically enriched but underutilized in prediction.

Learning to Defer framework extended to hierarchical multi-label medical imaging with coherence constraints preventing taxonomic contradictions.

Perceptual Flow Network mitigates vision-language model hallucination by eschewing rigid geometric priors for interpretable perceptual trajectories.

Google Gemini API adds webhook support for asynchronous job notifications, reducing polling overhead for long-running requests.

ORPilot: open-source agentic system translating ambiguous business problems into solver-ready optimization models with conversational and data collection agents.

PubMed-Ophtha: 102K ophthalmology image-caption pairs extracted from open-access PDFs for training vision-language models.

GRIDS framework uses Local Intrinsic Dimensionality to detect how perturbations deform representations in WavLM and wav2vec 2.0 models and track ASR degradation.

OphMAE is a multimodal foundation model bridging volumetric and planar ophthalmic imaging for adaptive diagnosis in resource-limited settings.