# High-Fidelity Simultaneous Speech-to-Speech Translation

**Hibiki** is a **decoder-only model** that enables **simultaneous speech translation** by processing source and target speech in real-time, producing both text and audio tokens for effective speech-to-speech translation.

# ChatGPT creates phisher's paradise by serving the wrong URLs for major companies

**AI chatbots, like ChatGPT, incorrectly provide URLs for major companies only 66% of the time, creating a fertile ground for phishing attacks.** This vulnerability arises as criminals exploit the AI's tendency to generate misleading links, potentially leading users to fraudulent sites.

# AV1@Scale: Film Grain Synthesis, The Awakening

**Netflix's AV1 Film Grain Synthesis (FGS) enhances streaming quality** by preserving the artistic integrity of film grain while achieving a **66% bitrate reduction**, allowing for high-quality video delivery with less data usage.

# About AI Evals

**RAG is not dead**; it remains vital for AI applications, but developers must distinguish between effective retrieval strategies and misleading marketing claims that oversimplify its utility. Understanding the nuances of **Retrieval-Augmented Generation** (RAG) is essential for making informed architectural decisions in AI systems.

# AI for Scientific Search

**AI4Research** presents a **comprehensive survey** on the application of **AI in scientific research**, addressing the lack of unified perspectives and systematic classifications in this rapidly evolving field.

# Ubuntu 25.10 Raises RISC-V Profile Requirements

**Ubuntu 25.10 elevates its RISC-V profile requirements from RVA20 to RVA23**, mandating essential features like **Vector and Hypervisor extensions**, which most current RISC-V devices lack, thus limiting compatibility with existing hardware.

# The End of Moore's Law for AI? Gemini Flash Offers a Warning

**Google's price increase for the Gemini 2.5 Flash model marks a pivotal shift in AI economics**, indicating that the era of consistently decreasing costs for AI intelligence may be over, as operational costs are now dictated by hardware limitations and demand dynamics.

# An Algorithm for a Better Bookshelf

A **new algorithm** for the bookshelf problem achieves an expected cost of **log _n_ × (log(log _n_))² per insertion**, significantly improving upon the previous log1.5 _n_ cost and approaching the theoretical lower limit of log _n_.

# Paper with code is completely down

**Paper with Code** is currently **completely down** after experiencing prior spam issues, indicating a significant disruption in access to machine learning research resources.

# Fast and Simplex: 2-Simplicial Attention in Triton

The **2-simplicial Transformer** architecture enhances token efficiency by utilizing trilinear functions, outperforming standard Transformers in tasks like **mathematics**, **coding**, and **reasoning**.

# Self-Correction Bench: Revealing and Addressing the Self-Correction Blind Spot in LLMs

**Self-Correction Blind Spot**: LLMs struggle to correct their own outputs, with a **64.5% average blind spot rate** across 14 models, indicating a significant gap in their self-correction capabilities.

# Ring Quantization: Achieving 90% on CIFAR-10 with 2-bit Networks

The **Ring Quantization** method achieves **90% accuracy** on CIFAR-10 with **2-bit networks**, demonstrating unexpected robustness at low bit-widths, particularly with deeper architectures like ResNet-32.

# MOTIF: Modular Thinking via Reinforcement Fine-tuning in LLMs

**MOTIF** introduces a novel **reinforcement learning** method that enables large language models (LLMs) to generate reasoning tokens across multiple rounds, effectively overcoming the **context size limitation** inherent in traditional LLMs.

# FlowSpec: Continuous Pipelined Speculative Decoding for Efficient Distributed LLM Inference

**FlowSpec** introduces a **pipeline-parallel tree-based speculative decoding framework** that enhances distributed LLM inference efficiency by prioritizing important tokens and managing drafts effectively.

# MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent

**MemAgent** introduces a novel **agent workflow** that optimizes long-text processing by reading in segments and employing an **overwrite strategy** for memory updates, addressing the challenge of handling infinitely long documents efficiently.