Knowledge catalogue
arXiv:2506.07460v2 Announce Type: replace-cross Abstract: Sign language generation (SLG), also known as text-to-sign generation, aims to bridge the communication gap between signers and non-signers. U
arXiv:2606.27604v1 Announce Type: cross Abstract: In this paper we present a spectral optical inversion for skin for path tracing-based rendering of subsurface scattering. Skin is a complex multilayer
arXiv:2508.12410v3 Announce Type: replace-cross Abstract: Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for red
arXiv:2505.06668v2 Announce Type: replace Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion
arXiv:2606.28083v1 Announce Type: cross Abstract: Micro-expression recognition is challenging due to subtle and short-lived facial muscle movements. Existing methods rely heavily on apex-onset frames,
In the agentic era, the role of the database has fundamentally changed. It is no longer a passive repository; it’s a critical context engine designed to ground generative AI apps, models and power aut
arXiv:2606.28309v1 Announce Type: cross Abstract: Binary classification from positive-only samples is a variant of PAC learning in which the learner receives i.i.d. samples from the positive region of
arXiv:2602.09456v2 Announce Type: replace Abstract: We propose an algorithmic framework, Offline Estimation to Decisions (OE2D), that efficiently reduces contextual bandit learning with general reward
arXiv:2606.28166v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capability of large language models, reaching expert or e
arXiv:2505.22783v2 Announce Type: replace-cross Abstract: Reliable altitude estimation with frequency-modulated continuous wave (FMCW) radar altimeters is increasingly a challenge due to in-band inter
arXiv:2606.27510v1 Announce Type: cross Abstract: Activation patching is the primary tool in mechanistic interpretability. It attributes causal responsibility for a model behavior to each of its indiv
arXiv:2606.27462v1 Announce Type: cross Abstract: The global minimum-variance portfolio (GMVP) is the canonical decision built from an estimated covariance matrix, yet covariance estimators are univer
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The inevitable weakness of metrics There are plenty of useful
arXiv:2606.28190v1 Announce Type: cross Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data an
arXiv:2606.27739v1 Announce Type: new Abstract: Process reward models (PRMs) enhance the reasoning capabilities of large language models (LLMs) by providing fine-grained feedback, yet training PRMs ty
A think tank conducted research examining how the Space Force should respond to space warfare scenarios, with experts envisioning various ways satellites and spacecraft might be used in gray-zone or w
arXiv:2606.28149v1 Announce Type: cross Abstract: In-context segmentation (ICS) requires a model to segment target regions in a query image using only a few reference images and their corresponding ma
arXiv:2606.27757v1 Announce Type: new Abstract: Large language models (LLMs) have attracted widespread attention from academia and industry, yet their deployment raises critical security concerns rega
arXiv:2606.27981v1 Announce Type: new Abstract: We introduce a new, contextual, multilingual dataset called ToxiREX: Toxic REasoning in ConteXt. The dataset consists of threads of Reddit comments and
arXiv:2510.00705v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) often struggle with fine-grained perception, such as identifying small objects in high-resolution images or
arXiv:2605.25042v2 Announce Type: replace Abstract: Existing score-based methods for inverse problems often resort to approximate minimization of the KL divergence between the inversion distribution a
arXiv:2606.27947v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When a
arXiv:2606.28237v1 Announce Type: new Abstract: Quadruped robots have achieved remarkable locomotion, yet their behavioral repertoire remains confined to a few gaits--far from the expressive, companio
arXiv:2606.27832v1 Announce Type: new Abstract: Statistical adversarial detection (SAD) treats detection as a two-sample test. Given a reference set of clean examples (CEs) and a batch of queries, pot
arXiv:2606.28301v1 Announce Type: new Abstract: Inference-time scaling is a promising paradigm to improve generative models, especially when outputs must satisfy structural constraints or optimize dow
arXiv:2606.28273v1 Announce Type: new Abstract: Vision-language models must reconcile visual evidence with memorized world knowledge when the two conflict. How they resolve this conflict shapes the re
arXiv:2606.27841v1 Announce Type: cross Abstract: The widespread adoption of Artificial Intelligence (AI) has led to increasing concerns about energy consumption, yet there is a lack of standardized m
arXiv:2606.27698v1 Announce Type: cross Abstract: Automatic Speech Recognition systems are notoriously both sensitive to adversarial and benign perturbations. While this has been repeatedly demonstrat
arXiv:2606.28308v1 Announce Type: cross Abstract: Many two-player zero-sum games admit not a unique Nash equilibrium but a convex set of them: a polytope of profiles that all share the minimax value V
This article discusses recent open-source AI model releases and developments from three companies—Zyphra, Cohere, and Poolside—and their contributions to expanding the broader AI ecosystem. It likely
Nice example of the increasing benefits of open science and transparent methodologies when writing papers about AI. A big problem with research studies on AI models is that given how long the peer rev
Putin's cannon fodder: 'The average life expectancy of a new recruit—from arrival at a training ground to death in a combat zone—lies...between 10 days and 3 weeks. Once...sent onto the battlefield, R
TechCrunch on Sakana Fugu and the broader conversation around frontier AI access in Asia. Our position remains that AI is best developed together rather than hoarded. Sakana AI will continue contribut
To really move the needle in terms of innovation, like the era in Japan when you had companies like Sony or Panasonic come out, there are a few factors at play. One is that the nation needs to have a
Sakana AI's Fugu-Ultra model is now available through Vercel's AI Gateway, expanding access to this language model through Vercel's infrastructure. This integration allows developers to use Fugu-Ultra
This article explores the implementation and use of local coding agents—AI systems designed to autonomously write, test, and debug code on local machines without relying on external APIs. The piece li
Loop engineering refers to an iterative approach to AI system design that combines prompt engineering with robust system architecture, emphasizing that effective AI applications depend equally on how
François Chollet argues that art and science elevate humanity through the creative and discovery processes themselves, rather than through their final outputs or products. He emphasizes that the trans
The Trump administration claims that mass deportations will free millions of jobs for Americans by reducing foreigner competiton. In fact, in the first nine months of 2025, ICE operations led to at le
arXiv:2606.26467v1 Announce Type: new Abstract: We introduce TabPFN-CFM, a causal foundation model that can handle multiple causal problems. TabPFN-CFM predicts both causal structure and outcomes from
arXiv:2606.26212v1 Announce Type: new Abstract: A Graph Neural Network (GNN) framework for predicting the solvability of finite groups from their Cayley graph representations was introduced in [1]. In
arXiv:2606.27014v1 Announce Type: new Abstract: Joint Embedding Predictive Architectures (JEPAs) have recently emerged as a promising paradigm for world modeling by learning predictive dynamics in a l
A good chunk of Tokyo is also reclaimed from the bay, a process that continues to this day but has slowed down significantly (peak was in the 1960s-1970s alongside other major infrastructure buildups)
arXiv:2606.26718v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) captures rich spatiotemporal information about ventricular structure and motion, but conventional risk models u
arXiv:2606.26260v1 Announce Type: cross Abstract: In laser penetration welding, the assessment of penetration state and weld seam morphology plays a crucial role in determining the weld quality. This
arXiv:2606.26425v1 Announce Type: new Abstract: Humanoid robots could take on physically demanding, hazardous, and repetitive work in spaces built for humans. However, a useful robot for these spaces
arXiv:2601.01084v2 Announce Type: replace Abstract: We present a large-scale unmanned aerial vehicle (UAV)-based RGB and multispectral image dataset collected over paddy fields in the Vijayawada regio
arXiv:2606.20869v2 Announce Type: replace-cross Abstract: We present a holistic methodology for artificial intelligence algorithm and accelerator co-design, co-search, and co-generation (A3C3), which
arXiv:2606.26859v1 Announce Type: new Abstract: Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remai
arXiv:2606.26764v1 Announce Type: cross Abstract: Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shif
arXiv:2606.27106v1 Announce Type: cross Abstract: We present a novel approach for applying Large Language Models (LLMs) to threat assessment in the context of foreign peacekeeping missions. Building o
arXiv:2606.27226v1 Announce Type: new Abstract: Evaluating LLM outputs remains a major bottleneck in NLP: human evaluation is expensive and slow, lexical metrics correlate poorly with human judgments
arXiv:2606.16325v2 Announce Type: replace Abstract: Few-shot medical image segmentation methods typically assume a single ground-truth annotation, overlooking systematic variability across expert rate
arXiv:2606.26982v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into mental health support tools and other psychologically sensitive conversational app
arXiv:2606.26344v1 Announce Type: cross Abstract: Writing high performance kernels for AI accelerators requires deep expertise in tiling, instruction selection, data layout, and operator fusion placin
arXiv:2606.26698v1 Announce Type: cross Abstract: In today's fast-paced information era, logical fallacies, defined as defective patterns of reasoning, inevitably contribute to the growth of informati
arXiv:2606.26279v1 Announce Type: new Abstract: Cognitive tasks are organized by shared and specialized neural processes. Masked fMRI reconstruction provides a common self-supervised objective for qua
arXiv:2606.27321v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) have become a leading tool for interpreting the representations of vision foundation models, decomposing their polysemantic
arXiv:2606.26508v1 Announce Type: cross Abstract: Interacting with computers typically relies on traditional input devices such as keyboards, mice, and monitors, which can be cumbersome for users seek
arXiv:2606.26754v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) provides an efficient and explicit representation for novel view synthesis, enforcing stylistic coherence across view