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ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions

arXiv:2605.20087v1 Announce Type: cross Abstract: Conversational AI has now reached billions of users, yet existing datasets capture only what people say, not what they think. We introduce ThoughtTrac

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three of the things we are most excited about: 1. AGI accelerating research 2. AGI accelerating companies 3. personal AGI accelerating every…

DGX agent

three of the things we are most excited about: 1. AGI accelerating research 2. AGI accelerating companies 3. personal AGI accelerating everyone in achieving their goals today it was great to announce

industrysam-altman--x

20 May 2026

Industry

Three precedent-setting court rulings in China have said that employers replacing workers with AI is voluntary cost-cutting that does not justify mass layoffs (Catie Edmondson/New York Times)

Catie Edmondson / New York Times: Three precedent-setting court rulings in China have said that employers replacing workers with AI is voluntary cost-cutting that does not justify mass layoffs — A ser

industrytechmeme

Applications

Throwing Vines at the Wall: Structure Learning via Random Search

arXiv:2510.20035v3 Announce Type: replace-cross Abstract: Vine copulas offer flexible multivariate dependence modeling and have become widely used in machine learning. Yet, structure learning remains

applicationsarxiv-cs-lg

TIDE: Asymmetric Neural Circuits for Stabilized Temporal Inhibitory-Excitatory Dynamics

arXiv:2605.19403v1 Announce Type: new Abstract: Recent Continuous Thought Machine architecture decouples internal computation from external inputs via neural dynamics, but relies on multi-layer percep

Hardware

TIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload

arXiv:2605.20179v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive (AR) models, offering better hardware utilization an

hardwarearxiv-cs-cl

TideGS: Scalable Training of Over One Billion 3D Gaussian Splatting Primitives via Out-of-Core Optimization

model-releasesarxiv-cs-cv

arXiv:2605.20150v1 Announce Type: new Abstract: Training 3D Gaussian Splatting (3DGS) at billion-primitive scale is fundamentally memory-bound: each Gaussian primitive carries a large attribute vector

Tight Regret Bounds for Fixed-Price Bilateral Trade

arXiv:2504.04349v3 Announce Type: replace-cross Abstract: We examine fixed-price mechanisms in bilateral trade through the lens of regret minimization. Our main results are twofold. (i) For independen

Time-optimal neural feedback control of nilpotent systems as a binary classification problem

model-releasesarxiv-cs-lg

arXiv:2503.17581v2 Announce Type: replace-cross Abstract: A computational method for the synthesis of time-optimal feedback control laws for linear nilpotent systems is proposed. The method is based o

Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?

arXiv:2605.19196v1 Announce Type: new Abstract: Deep research agents increasingly automate complex information-seeking tasks, producing evidence-grounded reports via multi-step reasoning, tool use, an

To Call or Not to Call: Diagnosing Intrinsic Over-Calling Bias in LLM Agents

model-releasesarxiv-cs-ai

arXiv:2605.18882v1 Announce Type: cross Abstract: LLM agents exhibit a consistent tendency to over-call, invoking tools even in situations where none is needed. On the When2Call benchmark, six models

Hardware

🌍Today we release Mosaic, a probabilistic weather model that shifts the Pareto frontier of ML weather forecasting. It matches the skill of …

🌍Today we release Mosaic, a probabilistic weather model that shifts the Pareto frontier of ML weather forecasting. It matches the skill of state-of-the-art models while generating a 24-member, 10-day

hardwareemad-mostaque--x

Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 …

Today, we share a breakthrough on the planar unit distance problem, a famous open question first posed by Paul Erdős in 1946. For nearly 80 years, mathematicians believed the best possible solutions l

model-releasesopenai--x

Industry

Today, we’re sharing that a general-purpose internal @openai model achieved a breakthrough on one of the best-known combinatorial geometry p…

Today, we’re sharing that a general-purpose internal @openai model achieved a breakthrough on one of the best-known combinatorial geometry problems. Less than 1 year ago frontier AI models were at IMO

industrysam-altman--x

Token by Token, Compromised: Backdoor Vulnerabilities in Unified Autoregressive Models

arXiv:2605.19227v1 Announce Type: cross Abstract: Unified autoregressive models (UAMs) are transformer models that generate text as well as image tokens within a single autoregressive pass. Shared par

Topology-Optimized Pneumatic Soft Actuator: Design and Experimental Validation

arXiv:2605.20101v1 Announce Type: new Abstract: This paper demonstrates the computational design of soft elastomeric pneumatic actuators using nonlinear topology optimization. An existing density- and

researcharxiv-cs-ro

TORQ: Two-Level Orthogonal Rotation for MXFP4 Quantization

arXiv:2605.19561v1 Announce Type: cross Abstract: As Large Language Models (LLMs) advance toward practical deployment, the Microscaling FP4 (MXFP4) format has emerged as a cornerstone for next-generat

Toto 2.0: Time Series Forecasting Enters the Scaling Era

model-releasesarxiv-cs-ai

arXiv:2605.20119v1 Announce Type: cross Abstract: We show that time series foundation models scale: a single training recipe produces reliable forecast-quality improvements from 4M to 2.5B parameters.

Toward an AI-Powered Computational Testbed for Workforce Policy

arXiv:2605.19064v1 Announce Type: cross Abstract: Workforce transformations are difficult to forecast and costly to mismanage. In particular, the integration of artificial intelligence into knowledge

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

arXiv:2512.18552v2 Announce Type: replace-cross Abstract: While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivit

agentsarxiv-cs-ai

Toward User Comprehension Supports for LLM Agent Skill Specifications

arXiv:2605.19362v1 Announce Type: cross Abstract: Users often interpret and select agent skills through their exttt{SKILL.md} specifications. To protect users, existing audits mainly focus on maliciou

agentsarxiv-cs-ai

Towards Camera-Robust 3D Localization: Equation-Anchored Tool-Use for MLLMs

model-releasesarxiv-cs-cv

arXiv:2605.19528v1 Announce Type: new Abstract: 3D localization in Multimodal Large Language Models (MLLMs), including 3D object detection and 3D visual grounding, is fundamentally limited by camera i

Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation

arXiv:2511.01482v2 Announce Type: replace Abstract: Text-based automated Cognitive Distortion detection is a challenging task due to its subjective nature, with low agreement scores observed even amon

Towards Data-Efficient Video Pre-training with Frozen Image Foundation Models

arXiv:2605.19137v1 Announce Type: new Abstract: Video foundation models achieve strong performance across many video understanding tasks, but typically require large-scale pre-training on massive vide

researcharxiv-cs-cv

Towards Discovery of Polymers for Insulin Delivery via Physics-Grounded Agentic Workflows

arXiv:2605.18831v1 Announce Type: cross Abstract: Cold-chain storage limits access to insulin for hundreds of millions of people; a thermally protective patch polymer could help, but the design space

agentsarxiv-cs-lg

Towards Distillation Guarantees under Algorithmic Alignment for Combinatorial Optimization

arXiv:2605.20074v1 Announce Type: new Abstract: Distillation transfers knowledge from a large model trained on broad data to a smaller, more efficient model suitable for deployment. In structured pred

safetyarxiv-cs-lg

Towards Family-Grouped Hierarchical Federated Learning on Sub-5KB Models: A Feasibility Study of Privacy-Preserving ECG Monitoring for Ultra-Resource-Constrained Wearables

arXiv:2605.18862v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of death worldwide, and early detection of arrhythmias through continuous ECG monitoring on wearable

Tutorials

Towards Fine-Grained Robustness: Attention-Guided Test-Time Prompt Tuning for Vision-Language Models

arXiv:2605.19956v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have achieved significant zero-shot performance on downstream tasks with various fine-tuning adaptation met

tutorialsarxiv-cs-cv

Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction

arXiv:2605.20055v1 Announce Type: cross Abstract: Explicit software architecture models are essential artifacts for communicating, analyzing, and evolving complex software-intensive systems. In ROS~2-

agentsarxiv-cs-ai

Hardware

Towards Multi-Model LLM Schedulers: Empirical Insights into Offloading and Preemption

arXiv:2605.19593v1 Announce Type: new Abstract: Modern deployments of Large Language Models (LLMs) increasingly require serving multiple models with diverse architectures, sizes, and specialization on

hardwarearxiv-cs-ai

Towards Trust Calibration in Socially Interactive Agents: Investigating Gendered Multimodal Behaviors Generation with LLMs

arXiv:2605.19798v1 Announce Type: new Abstract: As Socially Interactive Agents (SIAs) become increasingly integrated into daily life, the ability to calibrate user trust to an agent's actual capabilit

Training-Free Bayesian Filtering with Generative Emulators

arXiv:2605.20028v1 Announce Type: new Abstract: Bayesian filtering is a well-known problem that aims to estimate plausible states of a dynamical system from observations. Among existing approaches to

Training Neural Networks with Optimal Double-Bayesian Learning

model-releasesarxiv-cs-ai

arXiv:2605.20009v1 Announce Type: cross Abstract: Backpropagation with gradient descent is a common optimization strategy employed by most neural network architectures in machine learning. However, fi

Trajectory Planning and Control near the Limits: an Open Experimental Benchmark on the RoboRacer Platform

model-releasesarxiv-cs-ro

arXiv:2605.19881v1 Announce Type: new Abstract: We present a modular framework to benchmark new and existing methods for trajectory planning and control in high-acceleration maneuvers that push autono

TrajectoryMover: Generative Movement of Object Trajectories in Videos

arXiv:2603.29092v3 Announce Type: replace Abstract: Generative video editing has enabled several intuitive editing operations for short video clips that would previously have been difficult to achieve

researcharxiv-cs-cv

TrajTok: Adaptive Spatial Tokenization for Trajectory Representation Learning

arXiv:2605.20134v1 Announce Type: new Abstract: Learning generalizable trajectory representations from raw GPS traces remains difficult because the data is continuous, noisy, and irregularly sampled.

Transformers Linearly Represent Highly Structured World Models

arXiv:2605.18847v1 Announce Type: cross Abstract: Do transformers, when trained on sequential reasoning traces, build internal models of the underlying task? And if so, does the structure of those int

Transforming Constraint Programs to Input for Local Search

arXiv:2605.19671v1 Announce Type: new Abstract: Applying local search algorithms to combinatorial optimization problems is not an easy feat. Typically, human intervention is required to compile the co

TravExplorer: Cross-Floor Embodied Exploration via Traversability-Aware 3-D Planning

model-releasesarxiv-cs-ro

arXiv:2605.19958v1 Announce Type: new Abstract: Zero-shot Object Navigation (ZSON) has shown promise for open-vocabulary target search in unseen environments, yet most existing systems remain tied to

Tribal AI lands $10M in seed funding to bring metadata-native agents to the enterprise

Enterprise software veterans have become all too familiar with the gap between flashy artificial intelligence demos and their performance in real-world production environments. The reality is that a l

agentssiliconangle

.@trq212 is a builder's builder. After research at MIT, exiting his company, raising millions for another, and exploring research threads as…

.@trq212 is a builder's builder. After research at MIT, exiting his company, raising millions for another, and exploring research threads as an SPC member, he's now on the team building Claude Code. H

model-releasesthariq--x

Trump has successfully censored most major US media. The US ranks #64 on the World Press Freedom index, which is below freedom. And it is ge…

Trump has successfully censored most major US media. The US ranks #64 on the World Press Freedom index, which is below freedom. And it is getting worse very soon. Sad to see that the US lacks checks a

researchyann-lecun--x

Industry

Trump wants $1B to protect White House ballroom from drones and other threats

The Trump administration has requested $1 billion from taxpayers for security additions on the White House campus, including for a new ballroom being constructed on the site of the former East Wing. T

industryars-technica

Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R

arXiv:2605.19539v1 Announce Type: new Abstract: Geometric foundation models hold promise for unconstrained dense geometry prediction from uncalibrated images. However, in current feed-forward designs,

researcharxiv-cs-cv

Trust or Abstain? A Self-Aware RAG Approach

arXiv:2605.18792v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves large language models (LLMs) by incorporating external evidence, but it also introduces knowledge confli

Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On

arXiv:2605.19035v1 Announce Type: new Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution. As these agents

Try it out today at http://devin.ai/auto-triage

Cognition AI is promoting an auto-triage feature or tool available at devin.ai/auto-triage, inviting users to test it. The tool likely automates the process of categorizing, prioritizing, or routing i

agentscognition-ai--x

TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents

arXiv:2602.11767v3 Announce Type: replace Abstract: Advances in large language models (LLMs) are driving a shift toward using reinforcement learning (RL) to train agents from iterative, multi-turn int