Accurate pre-order shipping cost estimation is crucial in e-commerce. RouteCost introduces a multi-stage framework that decomposes the problem into time-aware demand forecasting, fee-card-informed baseline pricing, residual correction, and proxy-based box-consolidation inference. Evaluated on over 250,000 orders across 260 products and 18 months, it improves predictive quality and calibration while preserving route-level interpretability.

This paper proposes an operator-aware mixed-precision tolerance calibration method that mines accumulated cloud GPU run data to automatically determine optimal absolute tolerances for tensor kernel correctness tests, achieving much tighter tolerances than hand-picked ones and significantly improving bug-detection recall.

LLMs deployed in critical systems pose risks due to their inability to forget sensitive data. This survey examines gradient-based unlearning methods, questioning whether they genuinely remove knowledge or merely suppress expression, highlighting security and robustness challenges.

This paper presents ARGO, a smart eyewear platform leveraging the STM32N6 microcontroller and its integrated NPU for on-device machine learning, minimizing latency and preserving privacy. Through holistic co-design of hardware, firmware, and AI, an optimized YOLOv11 model is deployed for real-time urban obstacle recognition, introducing Head-wise Parallel Attention (HPA) for efficient NPU execution. The model achieves mAP50-95 of 24 with only 2.483 MB memory footprint. The platform integrates multimodal sensors, runs at 10 FPS, and provides ~113 minutes of autonomy on a 200 mAh battery, demonstrating the feasibility of high-performance, privacy-preserving assistive devices.

This paper proposes DocOCR-Eval, an annotation-free evaluation framework for automatic OCR assessment and selection. It employs a three-staged correction and ranking strategy to approximate annotation-based tool ordering without ground-truth labels. Experiments show that aggregating multiple MLLMs improves alignment with human rankings, enabling reliable tool selection in label-limited settings.

This paper proposes a novel RL-guided NSGA-II algorithm enhanced with Gray Relational Coefficients (RL-NSGA-II-GRC) that improves convergence and diversity of Pareto fronts in multi-objective optimization. It achieves around 5.8% and 4.4% convergence improvements over NSGA-II on benchmarks and produces a smooth efficient frontier for NASDAQ portfolio optimization, identifying a maximum Sharpe ratio portfolio of 1.92.

A new reinforcement learning method, W2SPO, uses weak auxiliary models to inject short segments into LLM reasoning paths, improving performance and training speed on math reasoning tasks.

Recent growth in reinforcement learning (RL) requires diverse training environments. World models can simulate environment states, but autoregressive models suffer from left-to-right bias. Masked diffusion language models (MDLMs) overcome this via bidirectional anchor-aware denoising, achieving better coherence and rollout diversity than LLMs 4x their size. A GRPO training framework is introduced, achieving up to 47% absolute gains on zero-shot transfer to out-of-distribution environments. The dataset and code are open-sourced.

This paper introduces Generative Ontology Induction (GOI), a domain-agnostic framework that induces a generative blueprint—entities, dimensions, properties, relationships, and constraints—from a corpus of examples and exports it as a typed graph (six node types, seven edge types) in YAML/JSON. A novel evaluation metric, Node Coverage Score, measures structural coverage. Validation on four diverse ontologies shows 95-100% coverage with GOI prompting, while a generic template drops significantly on unfamiliar domains.

arXiv:2607.16200 presents agrepl, a CLI framework for deterministic replay of AI agent executions. Using a MITM proxy, it records external interactions and replays them in isolation, achieving perfect fidelity (F=1.0) and 98.3% latency reduction.

A new research paper introduces PlanFlip, a framework of four planning-phase prompt injection attacks against multi-agent LLM systems. The study finds that stronger models like GPT-5 are more vulnerable, homogeneous backbones create a correlated-agent blind spot, and reasoning-augmented models like DeepSeek-R1 resist attacks. Two defenses are proposed with high detection rates.

This paper provides a comprehensive review of GNN-based link prediction from a novel GNN perspective, proposing a taxonomy covering GCN, GAE, GAT, and GFormer architectures, highlighting applications in knowledge graphs and recommendations, and discussing challenges and future directions.

A new study introduces a cross-domain framework to test LLMs' risk attitudes under uncertainty, finding that most models exhibit stable and consistent risk preferences both within and across tasks, with a distribution more restricted than humans.

This study presents an open-source MATLAB framework for compact deep learning models for affective touch recognition in soft interactive companions. After exploring 468 CNN models, a 13.2k-parameter dilated 1D CNN achieved 75% test accuracy and 85% leave-one-subject-out cross-validation accuracy. A hybrid pipeline combining heuristic filtering and CNN classification enables real-time 20 Hz operation on a microcontroller, enabling privacy-preserving emotional touch interpretation.

This paper identifies a structured confound in RLHF: pairwise preference labels may reflect the rater's state under stress, leading to state-dependent shifts that differ from random noise. It proposes an audit framework with defined concepts, falsifiable predictions, and a pilot study plan for detecting such bias.

A quiet day on the surface, but packed with developments: US policy targets Chinese open models, Kimi K3 and Qwen 3.8 advance, agent-centric generalization gains traction, and models show superhuman math abilities.

A Nikkei study shows hidden debt at U.S. tech giants swelled eightfold in roughly four years to an estimated $1.65 trillion as AI investments ballooned, exceeding actual debt and making it tougher for investors to assess risk.

Gary Marcus argues that China's Kimi K3 model has caught up with US top models, disrupting American AI business models. He recounts his warnings since 2025 that the US focus on LLMs would lead to a tie, not victory. Marcus proposes seven strategic options, ranging from inaction to making AI a global public good via an international 'CERN for AI' initiative.

Portraify is an AI-powered headshot generator that lets users upload 1–3 everyday photos to get a studio-quality portrait in seconds. It offers a free tier with 3 portraits, paid plans starting at $9, and emphasizes privacy by not storing uploaded photos.

Hugging Face disclosed that attackers used an autonomous AI agent system to breach its production infrastructure, gaining access to internal datasets and credentials. The company is investigating potential impact on partners and customers, with no evidence of tampering with public models or datasets so far.

Concentrate is a managed LLM gateway that provides a single API to access over 130 models from major providers. It offers features such as model routing, spend tracking, security controls, and fallback redundancy, designed for teams scaling AI in production.

Sakana AI releases Fugu-Cyber, a new orchestration model for cyber defense, achieving state-of-the-art performance on CyberGym and CTI-REALM benchmarks. The article emphasizes that frontier models alone are insufficient for enterprise security, requiring specialized human expertise and deep integration. Sakana's Applied Enterprise team is collaborating with major Japanese institutions to deploy these models safely. Access to Fugu-Cyber is gated behind an application and approval process.

Local-first AI meeting notes for Google Meet that runs on your machine, uses your own API keys, no bot joins the call, proactive insights from your files, one-time $3 fee.

Cairn is a personal finance AI that accesses financial data read-only via the MCP protocol, ensuring security.

daft-physical-ai is a new open-source Python library built on Daft that provides ready-made operations for turning raw robot recordings into training-ready data. It currently supports hand tracking and reward scoring, with lazy batch execution and distributed processing.

A self-hosted AI notification filter for Telegram that uses LLMs to filter noisy chats and send only important alerts via ntfy, allowing users to keep notifications off without missing urgent messages.

A live technical index ranking AI agents, MCP servers, frameworks, and infrastructure by maintained adoption. Explore 247 verified records across 11 system classes.

Vidmoat is an AI-powered video editor that lets you edit by prompt. It features auto-cut, AI captions, text-to-edit, one-click shorts, and an MCP server that enables any AI agent (Claude, Cursor, etc.) to drive the entire editing pipeline end-to-end.

PounceDomains is an AI-powered domain sniper for the Namecheap Marketplace. It surfaces the best names from thousands of aftermarket auctions, scores and enriches every match with AI tuned to your taste, and alerts you instantly so you can bid in one click.

Cognition's Devin, an AI software engineer, can now run in Modal sandboxes via Devin Outposts, enabling customized environments with GPU support and fast cold-starts.