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The Spectral Geometry of Thought: Phase Transitions, Instruction Reversal, Token-Level Dynamics, and Perfect Correctness Prediction in How Transformers Reason

arXiv:2604.15350v1 Announce Type: new Abstract: We discover that large language models exhibit spectral phase transitions in their hidden activation spaces when engaging in reasoning versus factual re

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Research

The Synthetic Media Shift: Tracking the Rise, Virality, and Detectability of AI-Generated Multimodal Misinformation

DGX agent

arXiv:2604.15372v1 Announce Type: cross Abstract: As generative AI advances, the distinction between authentic and synthetic media is increasingly blurred, challenging the integrity of online informat

researcharxiv-cs-ai

20 Apr 2026

Hardware

The threat of analytic flexibility in using large language models to simulate human data

arXiv:2509.13397v3 Announce Type: replace-cross Abstract: Social scientists are now using large language models to create 'silicon samples': synthetic datasets intended to stand in for human responden

hardwarearxiv-cs-ai

The US Air Force cancels RTX's ground-control network for the US' next generation of GPS satellites after years of delays and cost overruns (Anthony Capaccio/Bloomberg)

Anthony Capaccio / Bloomberg: The US Air Force cancels RTX's ground-control network for the US' next generation of GPS satellites after years of delays and cost overruns — The Air Force on Monday canc

industrytechmeme

The whole point about free speech is the right to insult. The second you insist social norms are observed, free speech dies. @Nigel_Farage d…

The whole point about free speech is the right to insult. The second you insist social norms are observed, free speech dies. @Nigel_Farage does not understand this. Neither does he understand that wit

industryelon-musk--x

Agents

The World Leaks the Future: Harness Evolution for Future Prediction Agents

arXiv:2604.15719v1 Announce Type: new Abstract: Many consequential decisions must be made before the relevant outcome is known. Such problems are commonly framed as future prediction, where an LLM age

agentsarxiv-cs-ai

.@TheOnion is replacing Alex Jones' Infowars with the comedians behind 'Tim & Eric' and 'Nathan for You' — and finally paying Sandy Hook fam…

model-releasesanthropic--x

.@TheOnion is replacing Alex Jones' Infowars with the comedians behind 'Tim & Eric' and 'Nathan for You' — and finally paying Sandy Hook families after years of lies. 'What happened to them won't happ

Agents

there’s clearly some confusing conflicts + double-think going on in AI between: 1. Closed labs saying use our harness, it’s naturally post-t…

there’s clearly some confusing conflicts + double-think going on in AI between: 1. Closed labs saying use our harness, it’s naturally post-trained and gets the best out of models by being “in-distribu

agentsharrison-chase--x

Think Multilingual, Not Harder: A Data-Efficient Framework for Teaching Reasoning Models to Code-Switch

arXiv:2604.15490v1 Announce Type: new Abstract: Recent developments in reasoning capabilities have enabled large language models to solve increasingly complex mathematical, symbolic, and logical tasks

researcharxiv-cs-cl

🤖 This debate is largely a matter of productivity gains-@a_bergeaud's latest book is a must read to easily understand why ! 📈 With @BunelS…

🤖 This debate is largely a matter of productivity gains-@a_bergeaud's latest book is a must read to easily understand why ! 📈 With @BunelSimon @XJaravel @tmikaelsen @alexandraroulet J.Søgaard we found

researchyann-lecun--x

This is also consistent with what OpenAI said at the time! https://x.com/polynoamial/status/2046064264189026587?s=20

applicationsethan-mollick--x

This is also consistent with what OpenAI said at the time! https://x.com/polynoamial/status/2046064264189026587?s=20 @emollick We felt it was the right thing to do. People deserved to know what was co

this is probably the best writeup we have on what makes agents production grade - there’s a lot of failure modes for agents we’ve learned ov…

applicationsharrison-chase--x

this is probably the best writeup we have on what makes agents production grade - there’s a lot of failure modes for agents we’ve learned over the years, most of which are articulated here Also it’s b

Tim Cook is a legend. I am very thankful for everything he has done and I am very thankful for Apple.

Sam Altman expressed gratitude toward Tim Cook and Apple on X, characterizing Cook as a 'legend' and acknowledging his contributions to the company. The post reflects appreciation for Apple's impact,

industrysam-altman--x

Tim Cook out, John Ternus in: Apple names hardware boss its next chief executive

Apple Inc. announced today that John Ternus, its senior vice president of hardware engineering, will become chief executive officer on Sept. 1, succeeding Tim Cook, who will transition to executive ch

industrysiliconangle

Time-optimal Convexified Reeds-Shepp Paths on a Sphere

arXiv:2504.00966v2 Announce Type: replace Abstract: This article studies the time-optimal path planning problem for a convexified Reeds-Shepp (CRS) vehicle on a unit sphere, capable of both forward an

researcharxiv-cs-ro

Time to really give Kimi K2.6 a go. Thank you @ollama! Love the ollama cloud setup!

Time to really give Kimi K2.6 a go. Thank you @ollama! Love the ollama cloud setup! Kimi K2.6 raises the bar for open-source models. 🦙 available on Ollama's cloud! Try it with OpenClaw: ollama launch

model-releasesollama--x

To LLM, or Not to LLM: How Designers and Developers Navigate LLMs as Tools or Teammates

arXiv:2604.15344v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into design and development workflows, yet decisions about their use are rarely binary or pur

ToolSimulator: scalable tool testing for AI agents

You can use ToolSimulator, an LLM-powered tool simulation framework within Strands Evals, to thoroughly and safely test AI agents that rely on external tools, at scale. Instead of risking live API cal

applicationsaws-ml-blog

Tutorials

TopFeaRe: Locating Critical State of Adversarial Resilience for Graphs Regarding Topology-Feature Entanglement

arXiv:2604.15370v1 Announce Type: cross Abstract: Graph adversarial attacks are usually produced from the two perspectives of topology/structure and node feature, both of them represent the paramount

tutorialsarxiv-cs-lg

Topology-Driven Fusion of nnU-Net and MedNeXt for Accurate Brain Tumor Segmentation on Sub-Saharan Africa Dataset

arXiv:2604.15964v1 Announce Type: cross Abstract: Accurate automatic brain tumor segmentation in Low and Middle-Income (LMIC) countries is challenging due to the lack of defined national imaging proto

Towards In-Context Tone Style Transfer with A Large-Scale Triplet Dataset

arXiv:2604.16114v1 Announce Type: new Abstract: Tone style transfer for photo retouching aims to adapt the stylistic tone of the reference image to a given content image. However, the lack of high-qua

Towards Intrinsic Interpretability of Large Language Models:A Survey of Design Principles and Architectures

arXiv:2604.16042v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and

safetyarxiv-cs-ai

Towards Realistic Open-Vocabulary Remote Sensing Segmentation: Benchmark and Baseline

model-releasesarxiv-cs-cv

arXiv:2604.15652v1 Announce Type: new Abstract: Open-vocabulary remote sensing image segmentation (OVRSIS) remains underexplored due to fragmented datasets, limited training diversity, and the lack of

Towards Rigorous Explainability by Feature Attribution

arXiv:2604.15898v1 Announce Type: new Abstract: For around a decade, non-symbolic methods have been the option of choice when explaining complex machine learning (ML) models. Unfortunately, such metho

Towards Robust Endogenous Reasoning: Unifying Drift Adaptation in Non-Stationary Tuning

arXiv:2604.15705v1 Announce Type: new Abstract: Reinforcement Fine-Tuning (RFT) has established itself as a critical paradigm for the alignment of Multi-modal Large Language Models (MLLMs) with comple

safetyarxiv-cs-lg

Hardware

Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective

arXiv:2511.00739v3 Announce Type: replace Abstract: Agentic AI serving converts monolithic LLM-based inference to autonomous problem-solvers that can plan, call tools, perform reasoning, and adapt on

hardwarearxiv-cs-ai

Towards Universal Convergence of Backward Error in Linear System Solvers

arXiv:2604.16075v1 Announce Type: cross Abstract: The quest for an algorithm that solves an nimes n linear system in O(n^2) time complexity, or O(n^2 ext{poly}(1/epsilon)) when solving up to epsilon r

TPA: Next Token Probability Attribution for Detecting Hallucinations in RAG

arXiv:2512.07515v4 Announce Type: replace-cross Abstract: Detecting hallucinations in Retrieval-Augmented Generation remains a challenge. Prior approaches attribute hallucinations to a binary conflict

Training Flow Matching: The Role of Weighting and Parameterization

arXiv:2603.06454v2 Announce Type: replace Abstract: We study the training objectives of denoising-based generative models, with a particular focus on loss weighting and output parameterization, includ

Training Time Prediction for Mixed Precision-based Distributed Training

arXiv:2604.16145v1 Announce Type: cross Abstract: Accurate prediction of training time in distributed deep learning is crucial for resource allocation, cost estimation, and job scheduling. We observe

Tools

🔬 Training Transformers to solve 95% failure rate of Cancer Trials — Ron Alfa & Daniel Bear, Noetik

Noetik uses transformer neural networks and machine learning to improve cancer drug trial success rates, addressing the historically high failure rate (95%) in clinical development. The approach lever

toolslatent-space

Trajectory Planning for Safe Dual Control with Active Exploration

arXiv:2604.15507v1 Announce Type: new Abstract: Planning safe trajectories under model uncertainty is a fundamental challenge. Robust planning ensures safety by considering worst-case realizations, ye

safetyarxiv-cs-ro

Transfer Learning from Foundational Optimization Embeddings to Unsupervised SAT Representations

arXiv:2604.15448v1 Announce Type: cross Abstract: Foundational optimization embeddings have recently emerged as powerful pre-trained representations for mixed-integer programming (MIP) problems. These

Transformer Neural Processes - Kernel Regression

model-releasesarxiv-cs-ai

arXiv:2411.12502v4 Announce Type: replace-cross Abstract: Neural Processes (NPs) are a rapidly evolving class of models designed to directly model the posterior predictive distribution of stochastic p

TriagerX: Dual Transformers for Bug Triaging Tasks with Content and Interaction Based Rankings

arXiv:2508.16860v2 Announce Type: replace-cross Abstract: Pretrained Language Models or PLMs are transformer-based architectures that can be used in bug triaging tasks. PLMs can better capture token s

applicationsarxiv-cs-ai

TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis

model-releasesarxiv-cs-cl

arXiv:2505.24672v2 Announce Type: replace Abstract: Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploit

Truncated Kernel Stochastic Gradient Descent with General Losses and Spherical Radial Basis Functions

arXiv:2510.04237v5 Announce Type: replace Abstract: In this paper, we propose a novel kernel stochastic gradient descent (SGD) algorithm for large-scale supervised learning with general losses. Compar

safetyarxiv-cs-lg

Try it out

model-releaseselon-musk--x

Try it out Anyone telling you that you need to use Claude to run just about any OpenClaw spending a wacky 1000 or more per month is no expert you should trust. Use @Grok. Great pricing and 4.3 is in a

TTL: Test-time Textual Learning for OOD Detection with Pretrained Vision-Language Models

arXiv:2604.15756v1 Announce Type: new Abstract: Vision-language models (VLMs) such as CLIP exhibit strong Out-of-distribution (OOD) detection capabilities by aligning visual and textual representation

researcharxiv-cs-cl

TwinTrack: Post-hoc Multi-Rater Calibration for Medical Image Segmentation

arXiv:2604.15950v1 Announce Type: new Abstract: Pancreatic ductal adenocarcinoma (PDAC) segmentation on contrast-enhanced CT is inherently ambiguous: inter-rater disagreement among experts reflects ge

Two-Dimensional Deep ReLU CNN Approximation for Korobov Functions: A Constructive Approach

arXiv:2503.07976v2 Announce Type: replace-cross Abstract: This paper investigates approximation capabilities of two-dimensional (2D) deep convolutional neural networks (CNNs), with Korobov functions s

Local Ai

Two-Stage Framework for Efficient UAV-Based Wildfire Video Analysis with Adaptive Compression and Fire Source Detection

arXiv:2508.16739v2 Announce Type: replace Abstract: Unmanned Aerial Vehicles (UAVs) have become increasingly important in disaster emergency response by facilitating aerial video analysis. Due to the

local-aiarxiv-cs-cv

TwoHamsters: Benchmarking Multi-Concept Compositional Unsafety in Text-to-Image Models

model-releasesarxiv-cs-cv

arXiv:2604.15967v1 Announce Type: cross Abstract: Despite the remarkable synthesis capabilities of text-to-image (T2I) models, safeguarding them against content violations remains a persistent challen

UA-Net: Uncertainty-Aware Network for TRISO Image Semantic Segmentation

arXiv:2604.15542v1 Announce Type: new Abstract: Tristructural isotropic (TRISO)-coated particle fuels undergo dimensional changes and chemical reactions during high-temperature neutron irradiation. Po

Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters

arXiv:2604.15339v1 Announce Type: cross Abstract: Uncertainty, vagueness, and ambiguity are closely related and often confused concepts in human-robot interaction (HRI). In earlier studies, these conc

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation

arXiv:2511.02626v3 Announce Type: replace Abstract: Prior works have shown that fine-tuning on new knowledge can induce factual hallucinations in large language models (LLMs), leading to incorrect out

researcharxiv-cs-cl

UniEditBench: A Unified and Cost-Effective Benchmark for Image and Video Editing via Distilled MLLMs

model-releasesarxiv-cs-ai

arXiv:2604.15871v1 Announce Type: cross Abstract: The evaluation of visual editing models remains fragmented across methods and modalities. Existing benchmarks are often tailored to specific paradigms

Univariate Channel Fusion for Multivariate Time Series Classification

arXiv:2604.16119v1 Announce Type: new Abstract: Multivariate time series classification (MTSC) plays a crucial role in various domains, including biomedical signal analysis and motion monitoring. Howe

researcharxiv-cs-lg