All articles, most recently crawled first.
HarnessEval-W introduces an agentified evaluation pipeline for world models, using hierarchical sub-agents to decompose evaluations into transparent reasoning chains, benchmarked on 18 models to align with human preferences.
This paper explores how attention mechanisms in language models render latent variables accessible without a selective gate, identifying a demand-specific mid-depth window where attention-mediated gathering occurs.
This paper finds that prior audit and repair episodes in context reduce false alarms in LLM verifiers by shifting decision thresholds, with repair content and audit verdict complementarily affecting different model families.
AnyTalk generates 3D speech animations for arbitrary characters without requiring animation data by adapting video diffusion models through character-specific fine-tuning and optimizing blendshape parameters, with a real-time distilled variant.
This paper introduces the Travelling Thief Problem with Drone (TTP-D), which jointly optimizes ground routing, drone synchronization, and item selection using mixed-integer programming, metaheuristics, and attention-based deep reinforcement learning.
HiFi-BRep improves B-Rep generation by using a topology-aware encoder and single-stage decoder to jointly predict geometry and topology with differentiable constraints, enhancing structural validity and geometric fidelity.
This paper explores using retired GPUs to build low-cost clusters for serving LLaMA-70B, finding economic viability in regions with cheap electricity but highlighting potential high carbon emissions without clean energy sources.
SA-MRPO introduces a saturation-aware advantage reweighting technique for multi-reward policy optimization in reinforcement learning, improving performance on mathematical reasoning, adaptive reasoning, and coding benchmarks by focusing optimization on under-optimized objectives.
PRISM is a training-free test-time adaptation method that reverses low-rank affine noise distortions in audio-text models using frozen text prototypes, showing significant improvements under severe acoustic noise.
WorldRover is a scalable synthetic data engine that generates long-range, richly annotated video sequences with depth and camera motion to support training models for coherent world exploration.
A Wellington second-hand bookstore discovered bulk orders from a Canadian buyer suspected to be for AI training, leading to concerns about book destruction and copyright issues.
The 37signals Manager Playbook provides guidelines for managers at 37signals, covering expected responsibilities, leadership philosophies, and balancing people management with individual work.
Claude Code introduces a new /design skill (research preview) that enables users to create and edit UI artboards in the CLI and Desktop applications, built on artifacts, and then have Claude implement the designs.
A user shares their experience of purchasing the MSI DGX Spark, using it to run AI models like DeepSeek V4 Flash and DeepSeek Harness, and exploring Minimax H3 and Music features.
Agent Network Protocol (ANP) is an open-source communication protocol designed to enable secure, efficient interactions between AI agents, positioning itself as the HTTP of the Agentic Web era.
agmsg 1.2.0 has been released, introducing remote synchronization capabilities for inter-agent messaging across different machines, with end-to-end encryption and self-hosted sync server options.
GE Aerospace highlights significant productivity gains from using Devin, an AI software development tool, comparing its impact to providing a top instrument to a master musician.
Gregor Zunic introduces macOS Harness, a persistent Python tool that enables control over Mac tasks using the accessibility tree, AppleScript, screenshots, and coordinate input.
The article discusses how hardware accuracy is crucial for meaningful quantum computing, referencing recent papers on quantum advantage and validation on Quantinuum systems.
The article explains that Qwen 3.8 27B is shipped with xhigh reasoning as default to maximize benchmark performance, defending the decision as reasonable given the context of open model benchmarking.