All entries

Training Hybrid Block Diffusion Language Models with Partial Bidirectionality

arXiv:2607.02805v1 Announce Type: cross Abstract: High-throughput long-context generation is one of the central challenges for large language models. Generation is typically memory-bandwidth-bound rat

Training Verifiably Robust Agents Using Set-Based Reinforcement Learning

DGX agent

arXiv:2408.09112v2 Announce Type: replace Abstract: Reinforcement learning policies parametrized by deep neural networks have achieved strong performance for continuous control, yet even small input p

safetyarxiv-cs-lg

7 Jul 2026

Trajectory-Anchor Optimization for Overconfident Thermal Visual Place Recognition: Zero-Leakage OOD Auditing and Kidnapped-Robot Recovery

arXiv:2607.04745v1 Announce Type: cross Abstract: Modern thermal visual place recognition (TIR-VPR) frontends based on foundation models achieve remarkable closed-set retrieval but suffer from an over

safetyarxiv-cs-cv

Trajectory-Aware Information Matching for Multi-Step Gradient Inversion in Federated Learning

arXiv:2509.22082v3 Announce Type: replace Abstract: Federated learning enables distributed information sharing and collaborative model training without exposing raw client data. However, shared gradie

local-aiarxiv-cs-lg

Transcribe Arabic is built to bring frontier capabilities to the millions of Arabic speakers in business and developer communities. Built to…

Transcribe Arabic is built to bring frontier capabilities to the millions of Arabic speakers in business and developer communities. Built to handle code-switching, multiple dialects, and Arabic-accent

model-releasescohere--x

Transfer Learning in High-dimensional Ising Models

arXiv:2607.03005v1 Announce Type: new Abstract: In high-dimensional Ising model estimation, target sample sizes are often limited, and effectively using auxiliary binary datasets of unknown relevance

researcharxiv-cs-lg

Transferability Between Understanding and Generation in Unified Multimodal Models

arXiv:2607.04423v1 Announce Type: cross Abstract: Unified Multimodal Models (UMMs) integrate image understanding and generation within a single architecture, yet how the two tasks interact remains und

Transformer-Based Multi-Agent Reinforcement Learning for Networked Systems with Long-Range Interactions

arXiv:2511.13103v2 Announce Type: replace Abstract: Multi-agent reinforcement learning (MARL) has shown promise for large-scale network control, yet existing methods face two major limitations. First,

safetyarxiv-cs-lg

Transformer-based Multisensor Data Fusion of Ultrasonic Guided Wave and FBG-based Strain Measurements for Multitask Aerospace Structural Health Monitoring

arXiv:2607.02545v1 Announce Type: cross Abstract: Structural health monitoring (SHM) has emerged as an essential tool for ensuring the integrity and reliability of critical engineering structures, par

local-aiarxiv-cs-lg

Transformers with Physics-Informed Encodings and Simulation-Based Inference for Robust Detection of Eccentric Binary Black Holes in Pulsar Timing Array Data

model-releasesarxiv-cs-lg

arXiv:2607.03904v1 Announce Type: new Abstract: Pulsar timing arrays (PTAs) provide a unique window into nanohertz gravitational waves (GWs), but extracting astrophysical parameters from noisy, long-b

Transition Information Density: Morphological Trajectories, Synesthetic Perception, and Structured Interpolation in Neural Training (or: The Synesthetic AI)

arXiv:2607.03210v1 Announce Type: cross Abstract: Standard machine learning training presents data as discrete endpoint pairs, omitting the structure of the space between them. This paper introduces T

TransitNet: A Compact Attention-Augmented Deep Learning Framework for Low-SNR Transit Blind Searches

arXiv:2606.18932v2 Announce Type: replace-cross Abstract: Motivated by the observational incompleteness of intermediate-to-long-period Earth-size planets, we present TransitNet, a compact attention-au

Applications

Transplanting, inverting, and preventing a misalignment persona: method-conditional emergent misalignment in Qwen2.5

arXiv:2607.04510v1 Announce Type: cross Abstract: Emergent misalignment (EM) -- the broad misbehaviour a language model acquires after fine-tuning on narrow harmful data -- is mediated in Qwen2.5 mode

applicationsarxiv-cs-ai

TreeLoc++: Robust 6-DoF LiDAR Localization in Forests with a Compact Digital Forest Inventory

arXiv:2603.03695v2 Announce Type: replace Abstract: Reliable localization is essential for sustainable forest management, as it allows robots to revisit and monitor the status of individual trees over

researcharxiv-cs-ro

TREK: Distill to Explore, Reinforce to Refine

arXiv:2607.05339v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) is effective when the current policy already samples useful reasoning trajectories, but it stalls on hard pr

TrendFact: A Benchmark Towards Hotspot Perception in Automatic Fact-Checking

model-releasesarxiv-cs-cl

arXiv:2410.15135v5 Announce Type: replace Abstract: With the surge of online misinformation, Large Language Models (LLMs) and Reasoning Large Language Models (RLMs) serving as Automatic Fact-Checking

TRIAGE: Trustworthy Retrieval Instrumentation And Graph Evaluation

arXiv:2607.03447v1 Announce Type: cross Abstract: Knowledge graphs (KGs) that underpin Graph-based Retrieval-Augmented Generation (Graph-RAG) are increasingly built automatically by LLM-driven extract

Triple-Phase Multimodal Knowledge Aggregation Framework for Microbial Keratitis Subtype Diagnosis on Slit-Lamp Photography

model-releasesarxiv-cs-cv

arXiv:2607.03740v1 Announce Type: cross Abstract: Microbial keratitis requires rapid pathogen identification to guide treatment, but culture- and PCR-based diagnostics are slow and resource-intensive.

Agents

TRISTAR: Triple-Signal Stair Recognition and Vision-Only Indoor Navigation for Search-and-Rescue Micro-UAVs

arXiv:2607.03818v1 Announce Type: new Abstract: Indoor search-and-rescue (SAR) operations often require rapid situational awareness where GNSS signals are unavailable and human access is difficult or

agentsarxiv-cs-cv

Trust-Region Noise Search for Black-Box Alignment of Diffusion and Flow Models

arXiv:2603.14504v2 Announce Type: replace-cross Abstract: Optimizing the noise samples of diffusion and flow models is an increasingly popular approach to align these models to target rewards at infer

local-aiarxiv-cs-ai

Trust Region Policy Distillation

arXiv:2607.04751v1 Announce Type: cross Abstract: Big goals are hard to achieve all at once; breaking them into small steps is wiser. We present Trust Region Policy Distillation (TOP-D), which transfo

TrustCLIP: Learning Private Visual Features via Adversarial Reconstruction

arXiv:2607.04484v1 Announce Type: new Abstract: Vision and vision-language models rely on high-level visual representations that are increasingly used across recognition, retrieval, and multimodal rea

researcharxiv-cs-cv

TSP with Predictions: Heatmap to Tour with Provable Guarantees

model-releasesarxiv-cs-lg

arXiv:2607.03791v1 Announce Type: cross Abstract: The Traveling Salesperson Problem (TSP) has long served as a benchmark for evaluating the strength of optimization techniques in the classical theory

Tutorials

TT-Sparse: Learning Sparse Rule Models with Differentiable Truth Tables

arXiv:2603.07606v2 Announce Type: replace Abstract: Interpretable machine learning is essential in high-stakes domains where decision-making requires accountability, transparency, and trust. While rul

tutorialsarxiv-cs-lg

TubeLite: Lightweight Multi-Actor Spatio-Temporal Action Detection

arXiv:2607.04684v1 Announce Type: new Abstract: Spatio-temporal action detection in videos requires jointly localizing actors in space and identifying action boundaries over time. A common challenge i

researcharxiv-cs-cv

Turbo-Muon: Almost-Orthogonal Pre-Conditioning for Fast Muon Updates

arXiv:2512.04632v2 Announce Type: replace Abstract: Orthogonality-based optimizers, such as Muon, have recently shown strong performance across large-scale training and community-driven efficiency cha

Turning Off-Policy Tokens On-Policy: A Plug-in Approach for Improving LLM Alignment

arXiv:2607.04728v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training for large language models (LLMs) follows a efficient paradigm of 'rollout then update', which inevitably res

Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders

arXiv:2607.04487v1 Announce Type: cross Abstract: Neural autoregressive solvers for the Multi-Attribute Vehicle Routing Problem (MAVRP) reach competitive cost but offer no per-step justification, a pr

U-Joint CAAMS: Experimental Evaluation of a Universal-Joint Continuum Manipulator for Aerial Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.03321v1 Announce Type: new Abstract: Continuum manipulators mounted on multi-rotor UAVs enable compliant aerial manipulation, but payloads and propeller downwash amplify out-of-plane bendin

UI-MOPD: Multi-Platform On-Policy Distillation for Continual GUI Agent Learning

arXiv:2607.04425v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform int

Hardware

UK-based AI infrastructure startup Nscale secures a $900M line of credit to expand its data center buildout across Europe, the US, and the Asia Pacific (Mauro Orru/Wall Street Journal)

Mauro Orru / Wall Street Journal: UK-based AI infrastructure startup Nscale secures a 900M line of credit to expand its data center buildout across Europe, the US, and the Asia Pacific — Nscale raised

hardwaretechmeme

Industry

ULA's last six Atlas Vs can't launch anything besides Boeing's Starliner

ULA's last six Atlas V rockets are all reserved for Boeing's Starliner missions, with no other payloads contracted for these final launches. No Starliner flight dates are currently set as Boeing and N

industryars-technica

Agents

UN Secretary-General António Guterres calls for autonomous 'killer robots' to be 'banned by international law', a central issue in the US DOD-Anthropic clash (Sam Schechner/Wall Street Journal)

Sam Schechner / Wall Street Journal: UN Secretary-General António Guterres calls for autonomous “killer robots” to be “banned by international law”, a central issue in the US DOD-Anthropic clash — Ant

agentstechmeme

Unbiased Alignment for Large Language Models with Noisy Preferences

arXiv:2607.03248v1 Announce Type: cross Abstract: The alignment of large language models with human preferences is commonly achieved through Reinforcement Learning from Human Feedback or Direct Prefer

Uncertainty-Aware Abstention in Large Language Models with Provable Alignment Guarantees

arXiv:2607.04430v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in question answering (QA) systems, yet they may generate hallucinated or misaligned responses wi

safetyarxiv-cs-cl

Uncertainty-aware damage identification in short-span bridges via physics-informed variational autoencoder

model-releasesarxiv-cs-lg

arXiv:2607.05025v1 Announce Type: new Abstract: Vibration-based damage identification in civil infrastructure is a challenging, ill-posed inverse problem due to measurement noise, sparse sensor arrays

Uncertainty-Aware Last-Layer Adaptation of RETFound for Referable Diabetic Retinopathy Screening Under Dataset Shift

arXiv:2607.02569v1 Announce Type: new Abstract: This paper presents a safety-centered empirical evaluation of uncertainty-aware last-layer adaptation for referable diabetic retinopathy screening using

safetyarxiv-cs-cv

Uncertainty Quantification for Regression: A Unified Framework based on kernel scores

arXiv:2510.25599v2 Announce Type: replace Abstract: Regression tasks, notably in safety-critical domains, require reliable uncertainty quantification, yet the literature remains largely classification

safetyarxiv-cs-lg

Understanding electricity consumption behaviour through Inverse Reinforcement Learning

arXiv:2607.03176v1 Announce Type: new Abstract: Understanding how households consume electricity in response to socioeconomic and climatic drivers is important for decision-makers designing energy pol

researcharxiv-cs-lg

UNDREAM: Bridging Differentiable Rendering and Photorealistic Simulation for End-to-end Adversarial Attacks

arXiv:2510.16923v3 Announce Type: replace-cross Abstract: Deep learning models deployed in safety critical applications like autonomous driving use simulations to test their robustness against adversa

Unified Audio Intelligence Without Regressing on Text Intelligence

arXiv:2607.05196v1 Announce Type: cross Abstract: Audio intelligence involves understanding, reasoning about, and generating both audio and speech. In this work, we introduce Nemotron-Labs-Audex-30B-A

Unified convergence analysis for gradient descent optimization methods in the training of deep neural networks

arXiv:2607.04233v1 Announce Type: cross Abstract: Gradient based optimization methods are nowadays the methods of choice for training deep neural networks (DNNs) in artificial intelligence (AI) system

researcharxiv-cs-lg

UniICL: Systematizing Unified Multimodal In-context Learning through a Capability-Oriented Taxonomy

model-releasesarxiv-cs-cv

arXiv:2603.24690v2 Announce Type: replace Abstract: In-context learning (ICL) enables fast task adaptation from demonstrations without per-task parameter updates but remains highly sensitive to exampl

UniSkip-Mamba: A Frequency-Aware State Space Model for Audio-Visual Temporal Forgery Localization

arXiv:2607.04498v1 Announce Type: new Abstract: With the proliferation of AI-generated content, sophisticated multimedia manipulation has raised critical concerns about malicious applications such as

local-aiarxiv-cs-cv

UniSpine-GS: An Efficient Physics-Aware Gaussian Framework for Cross-Modality Multi-view Spine Image Synthesis

arXiv:2607.04923v1 Announce Type: new Abstract: The diagnosis of spinal diseases is often assisted by 3D imaging techniques in clinical practice. However, precise 3D spinal assessment is limited by th

researcharxiv-cs-cv

Agents

UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation

arXiv:2607.05133v1 Announce Type: new Abstract: World Action Models (WAMs) have shown strong potential for improving action generalization in autonomous driving by using future video prediction as den

agentsarxiv-cs-cv

UniVideo: Unified Understanding, Generation, and Editing for Videos

model-releasesarxiv-cs-cv

arXiv:2510.08377v4 Announce Type: replace Abstract: Unified multimodal models have shown promising results in multimodal content generation and editing but remain largely limited to the image domain.

Unsupervised Behavioral Compression: Learning Low-Dimensional Policy Manifolds through State-Occupancy Matching

arXiv:2603.27044v3 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) is widely recognized as sample-inefficient, a limitation attributable in part to the high dimensionality and