AI/ML arXiv cs.AI

Numbers Already Carry Their Own Embeddings

Adelic operation-preserved embeddings (AOE) offer a training-free way to represent numbers in AI, preserving mathematical structures for better algebraic reasoning.

AI/ML arXiv cs.AI

A Two-Stage Statistical Framework for Evaluating Associative Interference in Large Language Models

A statistical framework for evaluating associative interference in LLMs shows that bias and interference vary significantly across models like GPT-5 and Claude.

AI/ML Hacker News

Anthropic's Safety Superpower

A discussion regarding Anthropic's approach to AI safety and its perceived efficacy.

Software Engineering Hacker News

Ported my C game to WASM, here's everybug that I hit

A developer shares the technical challenges and bugs encountered when porting a C game to WebAssembly (WASM).

Software Engineering Hacker News

Show HN: I wrote a C++ ray tracer from scratch without AI

A developer demonstrates building a C++ ray tracer from scratch without the use of AI tools.

Other The Verge

All the gear a 20-year gadget blogging veteran packs when traveling

A veteran gadget blogger shares their curated list of travel gear and accessories.

Hardware/Chips The Verge

Honor’s Magic V6 sets three foldable firsts

Review of the Honor Magic V6 foldable phone, noting its hardware improvements in thickness and battery.

AI/ML arXiv cs.AI

STREAM: Multi-Tier LLM Inference Middleware with Dual-Channel HPC Token Streaming

Introduction of STREAM, a multi-tier LLM inference middleware that optimizes routing between local, HPC, and cloud resources.

AI/ML arXiv cs.AI

Mask, Sample, Revise: A Revisable CTMC Inference Stack for Guided Discrete Flow Matching Text-to-Speech

A new inference stack for Guided Discrete Flow Matching Text-to-Speech to improve intelligibility and robustness.

AI/ML arXiv cs.AI

Hidden in Plain Sight: Benchmarking Agent Safety Against Decomposition Attacks with DECOMPBENCH

Introduction of DeCompBench, a benchmark for evaluating LLM agent safety against decomposition attacks.

AI/ML Hacker News

Openrouter Fusion API

OpenRouter introduces a Fusion API, likely enabling combined or aggregated responses from multiple AI models.

Tech Business/VC Hacker News

Foreign business owners are scrambling to raise capital to stay in Japan

Foreign business owners in Japan are facing capital raising challenges to sustain their operations.

Tech Business/VC Hacker News

Anthropic flies staff to D.C. to clean up White House fight

Anthropic staff are traveling to D.C. to address conflicts involving the White House.

AI/ML arXiv cs.AI

Crypto x AI, AI x Crypto: A Survey

A survey paper examining the integration and mutual benefits of AI and blockchain technology, noting they are in early stages.

AI/ML arXiv cs.AI

Gefen: Optimized Stochastic Optimizer

Introduction of Gefen, a memory-efficient stochastic optimizer that reduces AdamW's memory footprint by ~8x without performance loss.

AI/ML arXiv cs.AI

How do Self-Supervised Remote Sensing Vision Models Transfer to Downstream Tasks?

A study on how self-supervised remote sensing vision models transfer to downstream geospatial tasks and their internal representation organization.

AI/ML arXiv cs.AI

HiLo-Token: Input-Adaptive High-Low Frequency Token Compression for Efficient Image Editing

HiLo-Token is a token compression framework for image editing that optimizes latency in Diffusion Transformers by adaptively allocating tokens based on frequency.

AI/ML arXiv cs.AI

SANA: What Matters for QA Agents over Massive Data Lakes?

SANA is a diagnostic ablation framework designed to evaluate and identify bottlenecks in LLM agents performing question answering over massive data lakes.

AI/ML arXiv cs.AI

GMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging

GMN4AD is a Graph Matching Network used for Alzheimer's Disease diagnosis using sMRI data, featuring test-time domain adaptation.

AI/ML arXiv cs.AI

The Silent Cost of Artificial Intelligence Assistance: A Theory of Autonomy Surrender, the Recovery Mechanism, and the Restoration of Human Agency

A theoretical paper discussing the 'silent cost' of AI assistance, where humans gradually surrender autonomy and agency to AI systems.