The Archive

GraRe re-ranks 6-DoF grasp candidates using geometry and object context without modifying frozen detectors, improving alignment with actual grasp quality.

Benchmarking PPG-based sleep staging datasets and metrics, showing substantial performance gap vs. EEG and advocating finer temporal resolution.

Analysis of entropy inversion in LLM temperature scaling: autoregressive feedback drives 11 models through entropy maximum into population inversion and nonlinear dynamics.

Neuro-symbolic governance framework for verifiable AI agents in decentralized digital twin ecosystems with semantic profile layers.

xMICD balances interpretability and performance in ICD code representation for clinical risk prediction via embedding-based explainability.

Gaokerena: compact Persian-language medical LLM family trained on 90M-token corpus for low-resource healthcare deployment.

LAND model simulates 314K heterogeneous agents and human actors over 30 days to study emergent social dynamics via LLM-enabled ABM.

Calibration breaks under unseen subtype shift: models maintain accuracy but become systematically overconfident on novel fine-grained categories.

RefactorAssist agentic system improves LLM code refactoring reliability by detecting and correcting functional behavior changes pre-deployment.

Tevatron 3.0 integrates Megatron-Core for efficient MoE reranker training, enabling billion-scale cross-encoder + distillation workflows on academic budgets.

UpliftBench reveals metric disagreement, not model disagreement, drives uplift estimator ranking variance across 7 dataset families and 12 methods.

FinHardBench evaluates LLM-generated FPGA hardware for financial trading (latency-critical 5-10ns); 33 tasks span module generation, pipeline tuning, adaptation.

Physics-informed action-space reshaping for network control learns to exclude suboptimal placements before value function optimization, reducing search.

Greg Brockman (OpenAI) notes ChatGPT-Slack integration friction: users reject AI-initiated requests, prefer AI enhances rather than replaces human interaction.

datasette-apps 0.2a0 adds app_debug() and app_list() tools to enable agentic creation and testing of web apps via sandboxed iframe execution.

OpenAI's internal Astra model solved ten decade-old math problems for under $2K, matching Anthropic's cryptographic findings with Claude.

Despite a lawsuit from xAI, a Minnesota ban on apps that allow users to “nudify” images can move forward.

Green offered a remarkable apology, saying that "the level of dopamine that I've been getting from interacting with LLMs ... is not healthy for me or good for the world."

That cover art is almost certainly AI, too. | Image: Fenix Flexin Fenix Flexin is best known as a member of Shoreline Mafia, a rap duo from Los Angeles. But he's recently found solo success with the track "Rubberz," which has climbed to number 58 on the Billboard Hot 100. Almost immediately, though, questions were raised about the song's origins, with many speculating that it was largely, if not entirely, generated by AI. Fenix has denied those accusations, but done little to dispel them. Part of the suspicion is certainly due to the fact that the song is a dramatic left turn. Fenix has prima...

OpenAI's CEO seemed excited to share a "cool use case" for parents.

Reddit may still be considering ending its licensing deal with Google.

DeepSeek V4-Flash 0731 released; minimal other activity.

OpenAI reports progress on open problems in geometry, cryptography, and complexity theory using AI methods.

DeepSeek releases V4-Flash-0731, a 304B parameter model with enhanced agentic capabilities, outperforming larger competitors at $0.14/$0.27 per million tokens.

MCP 2.0 (stateless Model Context Protocol) launches with significant spec changes; Simon Willison revives mcp-explorer and datasette-mcp tooling.

Simon Willison releases llm-mcp-client 0.1a0, enabling Model Context Protocol integration for LLM tools.

OpenAI has reportedly found evidence of additional agent misbehavior as it looks into the incident that occurred with Hugging Face.

As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because... As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because attention now dominates that cost, how it is designed—not just how it is implemented—increasingly determines a model’s inference performance. Shaping model architecture around how GPUs execute it is the premise of AI model co-design. Source

Podcast discussion on open-weight model competitiveness, cybersecurity risks, and AI leadership policy letters signed by industry leaders.

Reddit advances lawsuit accusing Perplexity AI of conspiring with web scraper.