All entries

arXiv:2602.02979v2 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated strong potential in complex reasoning, yet their progress remains fundamentally constrained by reliance

arXiv:2605.18413v1 Announce Type: new Abstract: Automated structural health monitoring is essential to prevent catastrophic infrastructure failures. Precise, pixel-level defect segmentation is needed

arXiv:2605.16799v1 Announce Type: cross Abstract: Recent advances in molecular representation integrates molecular topological and visual modalities, opening new avenues for precise Molecular Relation

arXiv:2605.16806v1 Announce Type: cross Abstract: Collaborative game-based learning environments offer rich opportunities for small-group knowledge construction, yet automatically predicting student c

arXiv:2605.16373v1 Announce Type: cross Abstract: Early and accurate diagnosis and lesion localization of bone infections are crucial for clinical treatment. PET-CT integrates anatomical information f

arXiv:2605.18621v1 Announce Type: cross Abstract: Spatial intelligence requires multimodal large language models (MLLMs) to move beyond single-view perception and reason consistently about objects, vi

arXiv:2605.16431v1 Announce Type: new Abstract: Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet C

arXiv:2603.21071v2 Announce Type: replace-cross Abstract: As one of the most important underwater sensing technologies, forward-looking sonar exhibits unique imaging characteristics. Sonar images are

arXiv:2603.01993v2 Announce Type: replace Abstract: Recent advances in generative AI have significantly enhanced the realism of multimodal media manipulation, thereby posing substantial challenges to

arXiv:2603.02642v2 Announce Type: replace Abstract: Robust trajectory optimization enables autonomous systems to operate safely under uncertainty by computing control policies that satisfy the constra

Curious finding while creating evals and benchmarks for long-horizon (100+ turn) agents While it’s generally thought that a direct swap to open source models can bring immediate cost savings, that’s n

arXiv:2605.17807v1 Announce Type: cross Abstract: Text-to-Image (T2I) generation has achieved remarkable progress in recent years. Meanwhile, reinforcement learning methods, particularly those based o

Cursor is now available in Jira. Assign Cursor to work items, or mention @​Cursor in a comment to kick off a cloud agent. Cursor uses the title, description, comments, and your team's repository setti

customers are increasingly asking us for certainty on capacity. as models get better, we expect that the world will be capacity-constrained for some time. we are offering discounted tokens for 1-3 yea

arXiv:2602.03012v2 Announce Type: replace-cross Abstract: Evaluating and improving the security capabilities of code agents requires high-quality, executable vulnerability tasks. However, existing wor

arXiv:2605.17305v1 Announce Type: new Abstract: Large language model (LLM) self-correction -- the ability to detect and fix errors in generated outputs -- remains largely ad hoc, relying on generic pr

arXiv:2605.17037v1 Announce Type: cross Abstract: Reinforcement learning (RL) has demonstrated potential for enhancing reasoning in large language models (LLMs). However, effective RL training, which

arXiv:2605.16342v1 Announce Type: cross Abstract: Diffusion large language models are a compelling alternative to autoregressive models, yet existing RL methods for diffusion treat all denoising steps

arXiv:2605.17866v1 Announce Type: new Abstract: Small-scale data is a critical problem in time-series forecasting tasks. Data augmentation is an effective strategy for this task, but it has a limitati

arXiv:2605.18608v1 Announce Type: new Abstract: Continual Test-Time Adaptation (CTTA) aims to empower perception systems to handle dynamic distribution shifts encountered after deployment. Existing me

arXiv:2605.18102v1 Announce Type: new Abstract: Monocular video human mesh recovery is essential for digital humans, avatar animation, and embodied simulation, where both temporal stability and expres

arXiv:2603.08145v2 Announce Type: replace-cross Abstract: Preference-based alignment methods (e.g., RLHF, DPO) typically optimize a single scalar objective, implicitly averaging over heterogeneous hum

arXiv:2605.18298v1 Announce Type: new Abstract: Foundation models pre-trained through masked reconstruction on large-scale EEG data have emerged as a promising paradigm for learning generalizable neur

Artificial intelligence fraud prevention platform company Darwinium UK Ltd. today released updates to its Android and iOS mobile software development kits, adding continuous in-session detection of re

arXiv:2508.13309v3 Announce Type: replace Abstract: Numerous techniques have been proposed for generating adversarial examples in white-box settings under strict Lp-norm constraints. However, such nor

arXiv:2605.18753v1 Announce Type: cross Abstract: Current hierarchical attention methods, such as NSA and InfLLMv2, select the top-k relevant key-value (KV) blocks based on coarse attention scores and

arXiv:2605.16298v1 Announce Type: cross Abstract: While traditional AI and data-driven facilities management approaches have improved building operational efficiency, they remain constrained by centra

arXiv:2605.18720v1 Announce Type: new Abstract: Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. T

arXiv:2605.18635v1 Announce Type: cross Abstract: Credit default prediction is a tabular learning problem with severe class imbalance, heterogeneous features, and tight latency budgets. Tabular Founda

Databricks has launched the Context Engineer Associate certification, described as the industry's first credential specifically designed for professionals building reliable AI agent systems. The certi

datasette-llm is a plugin that integrates LLM functionality into Datasette for language model operations. Version 0.1a8 represents an alpha release of this plugin that extends Datasette's capabilities

datasette-llm-accountant is a plugin that handles allowances and estimated pricing features for Datasette LLM usage. It works with datasette-llm and datasette-llm-limits to let users configure spendin

arXiv:2605.18498v1 Announce Type: cross Abstract: Expert specialization in Mixture-of-Experts (MoE) models remains poorly understood, with traditional evaluations conflating architectural load-balanci

arXiv:2605.17899v1 Announce Type: cross Abstract: AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This st

Artificial intelligence developer Decart.ai Inc. today announced that it has raised 300 million in funding at a nearly 4 billion valuation. Radical Ventures led the round with participation from Nvidi

arXiv:2605.16989v1 Announce Type: new Abstract: Individualized treatment selection with continuous actions requires accurate causal response estimation in decision-relevant regions, rather than unifor

arXiv:2411.17917v2 Announce Type: replace Abstract: Motion prediction is critical for autonomous vehicles to effectively navigate complex environments and accurately anticipate the behaviors of other

arXiv:2605.16807v1 Announce Type: new Abstract: In this paper, we introduce extit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for

arXiv:2406.13187v2 Announce Type: replace Abstract: While long-tailed semi-supervised learning (LTSSL) has attracted growing attention in many real-world classification tasks, existing LTSSL algorithm

arXiv:2605.18354v1 Announce Type: new Abstract: Bayesian conformal optimisation methods often use the same held-out data both to search for efficient prediction sets and to certify coverage or risk. T

arXiv:2510.21712v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems have emerged as a pivotal methodology for enhancing Large Language Models (LLMs) through the dyna

arXiv:2605.16826v1 Announce Type: cross Abstract: Knowledge distillation is central to LLM post-training, yet its design space remains poorly understood, especially alongside reinforcement learning (R

arXiv:2603.00952v2 Announce Type: replace Abstract: High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated t

Deep Agents now integrates with @nebiusai Token Factory. Now, you can run agent workloads on production-grade AI infrastructure with open-source models, dedicated endpoints, real-time search, and full

arXiv:2601.06858v2 Announce Type: replace-cross Abstract: Future wireless communication systems will increasingly rely on the integration of millimeter wave (mmWave) and sub-6 GHz bands to meet hetero

arXiv:2605.17668v1 Announce Type: new Abstract: Implementation of digital pathology leads to an increased number of whole slide images (WSIs). The large size of WSIs is challenging. Today, WSIs are co