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Your AI agents just got a stricter teacher, and drones are now spying at 5 GHz.
Catch you tomorrow, and keep hacking the future.
Agentic on-policy distillation suffers from teacher myopia: next-token scores let safe, delaying moves pass, causing students to run out of turns despite teacher takeovers succeeding.
Previous remedies focused on keeping training within regions where the teacher is reliable, using curricula or interventions. This work shows that even when the teacher can complete tasks after student divergence, its token-level scoring fails to penalize delayed actions, highlighting a limitation of outcome-agnostic scoring.
CoRAL combines a diffusion planner that generates K parallel reasoning paths with an autoregressive executor that selects the best plan, achieving competitive accuracy and higher efficiency on vision‑language benchmarks.
The planner uses Reward‑Guided Denoising to incorporate outcome‑based rewards into diffusion, steering generations toward goal‑directed reasoning. The executor, a large ARM, synthesizes the final answer from the chosen plan, closing the gap between parallelism and semantic coherence.
DecisionPivot is a diagnostic benchmark with 48 tasks and 40,033 items that evaluates decision models' accuracy, contrast‑group performance, calibration, and selective coverage.
The benchmark splits into a core track (7,800 items from 13 generated families) and a reference track (32,233 items from 35 public sets). It assesses 40 decision models and 14 general models, revealing substantial gaps in reliable decision‑making across variations.
FairStress provides an in‑depth evaluation of fairness in large language model decision‑making.
The Hugging Face blog post outlines a methodology for probing bias across multiple decision contexts, extending beyond standard accuracy metrics to examine disparate impact and subgroup performance.
Anthropic details new defenses designed to mitigate model distillation attacks.
The announcement describes technical measures such as watermarking, query throttling, and model‑output obfuscation intended to prevent adversaries from extracting proprietary model weights via repeated inference.
OpenAI reports that Terminal X’s evaluation agent matches senior investor judgment 88.6% of the time using GPT‑6.1, detecting 25% more mandate deviations.
The Eval Agent scores outputs against a 54‑criterion rubric, improving detection of compliance breaches compared to prior evaluation methods, suggesting higher alignment of GPT‑6.1 with investment guidelines.
Anthropic posted an Announcements section without additional content.
The source provides a heading but no accompanying text, so no specific information or updates are available.
Anthropic released a Features update with no details provided.
The entry lists a title but contains no descriptive text, leaving the nature of the features unspecified.
A Schlotzsky’s and Cinnabon franchisee reduced menu repricing time by 95% using a ChatGPT workflow, potentially freeing $100K cash flow.
The workflow automates price updates across the menu, cutting manual effort dramatically. This efficiency gain translates into significant operational savings and faster response to market changes.
ALTK‑Evolve achieved top performance on the τ²‑bench customer service leaderboard using learned memory without a frontier model.
The approach leverages a memory‑augmented architecture to surpass larger models on specific tasks. It demonstrates that specialized memory mechanisms can replace scale‑based improvements in certain domains.
Hackaday reports a project using an ESP32’s hidden SDR to capture 5 GHz drone video.
The ESP32 series now reveals software‑defined radio capabilities, enabling hobbyists to process high‑frequency video streams. The project showcases practical use of this newfound feature for drone footage.
OpenBSD 8.0 released, adding arm64 hibernate, 512 GB amd64 kernel address space, and Qualcomm Wi‑Fi 6 driver improvements.
The new version expands virtual memory limits for amd64 platforms and introduces power‑saving hibernate support on ARM64 devices. Additional driver updates enhance stability and performance for modern Wi‑Fi hardware.
Kernel developer Daniel Gomez proposed rewriting XArray data structures in Rust to reduce bugs, citing potential security and performance gains.
The discussion took place at Kangrejos 2026, where kernel developers expressed caution about replacing the mature XArray code. Rust's safety guarantees are seen as a way to mitigate bugs in the complex XFS block‑size handling.
SUSE security lead Thorsten Kukuk advocated disabling setuid and setgid binaries across the entire system.
At the 2026 All Systems Go! conference he outlined the challenges of removing these legacy mechanisms, which are traditionally avoided but still present in many packages unless explicitly approved.
Mozilla reported that private keys for eight eMudhra intermediate certificates were compromised and revoked them via OneCRL and NSS 3.131.1.
The compromised keys could enable fraudulent HTTPS certificates. Chrome blocked the certificates on October 17, Apple on the 19th, and Microsoft on the 20th, mitigating the risk across major browsers.
A Hackaday article describes building a full‑featured ground station for receiving satellite signals.
The piece contrasts quick‑and‑dirty Yagi setups with a more comprehensive approach, covering hardware choices and software integration for continuous satellite communication.
A Hacker News post notes that 2026 is expected to be a significant year for the Rust compiler.
The author anticipates major improvements and personal milestones in Rust development, though specific features or releases were not detailed in the post.
The SWatcher+ framework adapts learned cardinality estimators to dynamic database workloads by monitoring high‑impact subqueries and applying on‑the‑fly corrections.
By focusing on queries where estimation errors hurt plan performance, SWatcher+ reduces the need for costly full model retraining while balancing monitoring overhead.
The SAFE decision layer converts predicted runtimes into conservative walltime recommendations, evaluated on Fugaku (≈24 M jobs) and NREL Eagle (≈11 M jobs) production histories.
The framework treats runtime prediction as a modular component, allowing any predictor to be used. It aims to reduce overestimation that harms scheduling efficiency. Experiments show the decision layer improves resource utilization without needing a new predictor model.
The paper analyzes why serving long‑context LLMs on a single GPU locally is limited beyond model size, questioning the need for compression.
It examines memory, bandwidth, and algorithmic constraints across several models, rather than profiling a single model. Findings highlight trade‑offs between context length and latency, informing design of more efficient local inference pipelines.
A new calculus models first‑class environments and function application using standard record types, fully mechanized in Lean 4 with proofs of soundness and normalization.
The design extends general record types and includes mutable references, enabling a simple yet principled approach. An interpreter verified against the operational semantics demonstrates practical applicability of the theory.
A federated learning and knowledge distillation method trains head networks for split computing without requiring large labeled datasets on mobile devices.
The approach reduces communication and computation load on the device while preserving privacy, enabling more efficient distributed inference. Experiments show comparable accuracy to centrally trained heads with significantly less labeled data.
OpenCV is an open‑source computer‑vision library written in C++ providing a wide range of image and video processing functions.
The library is cross‑platform, supports hardware acceleration, and is widely used in research and industry for tasks such as object detection, face recognition, and augmented reality.
MicroManipulatorStepper is a C++ project offering a sub‑micrometer 3D motion‑control platform for precision positioning.
It provides hardware‑agnostic stepper control code and examples, targeting applications like microscopy, micro‑assembly, and research instrumentation where nanometer‑scale movement is required.
Beav is an AI operations toolkit for Xiaohongshu that bundles content collection, comment downloading, media library, topic selection, AI writing, and automatic image layout into a one‑click installable package.
The suite integrates a Xiaohongshu‑specific OpenClaw scraper, a media asset base, and AI‑assisted creation tools, supporting both text and image generation. It also includes utilities for other platforms like Douyin and generic web crawling, aiming to streamline self‑media workflows.
Omnigraph is a graph database built to run directly on object storage, offering native branching and a typed ontology model.
By leveraging object‑storage APIs, the system avoids traditional server‑side graph engines, enabling scalable versioned graph structures. Typed ontologies allow schema enforcement, while branching supports experimental data without affecting the main graph.
Voice‑Pro provides a Gradio WebUI that combines TTS engines (Edge‑TTS, kokoro) with zero‑shot voice cloning (E2, F5‑TTS, CosyVoice) and Whisper‑based audio processing.
The interface also supports YouTube video download, Demucs vocal isolation, and multilingual translation, targeting creators and developers who need an all‑in‑one speech synthesis and processing pipeline.
Open‑Ontologies lets users plan, apply, and roll back changes to production ontologies while generating a blast‑radius report and auditable proof.
The tool tracks modifications, estimates impact across dependent data, and produces documentation that auditors can verify, facilitating safer ontology evolution in enterprise settings.
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