Knowledge catalogue
arXiv:2602.04509v4 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on task-specific data is an effective way to improve performance on downstream applications. Ho
arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved
arXiv:2605.00994v1 Announce Type: new Abstract: Finetuning can significantly modify the behavior of large language models, including introducing harmful or unsafe behaviors. To study these risks, rese
arXiv:2506.05952v4 Announce Type: replace Abstract: Recent advances in transformer-based text-to-motion generation have led to impressive progress in synthesizing high-quality human motion. Neverthele
arXiv:2605.01954v1 Announce Type: cross Abstract: Many sequential decision-making problems exhibit hierarchical structure, where high-level semantic choices constrain downstream actions and feedback i
arXiv:2605.01822v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being used to support scientific discovery. In chemistry, tasks such as reaction prediction and structure
arXiv:2605.02881v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today's systems fall short on the criteria that matter
arXiv:2605.02351v1 Announce Type: new Abstract: Molecular Vibe Coding, a paradigm where chemists interact with LLMs to generate executable programs for molecular tasks, has emerged as a flexible alter
arXiv:2605.02292v1 Announce Type: new Abstract: Chest X-ray classification suffers from severe class imbalance where gradient updates bias toward majority classes, causing feature drift and poor perfo
arXiv:2605.02521v1 Announce Type: new Abstract: Affective image editing (AIE) aims to edit visual content to evoke target emotions. However, existing methods often overlook inference efficiency and pr
More governments and public agencies should use HF and open-source AI in general. Let’s go sovereign AI! Cumhurbaşkanlığı İletişim Başkanlığımız, dünyanın en büyük yapay zekâ ve makine öğrenmesi toplu
arXiv:2507.14061v2 Announce Type: replace Abstract: What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat the
arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding
Most AI tools are a black box. You put something in and have limited say over what happens in between. For production pipelines, that's a dealbreaker. Silverside, an AI innovation lab running full pro
arXiv:2605.01725v1 Announce Type: new Abstract: Autoregressive video generation paradigms offer theoretical promise for long video synthesis, yet their practical deployment is hindered by the computat
arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in
arXiv:2605.02689v1 Announce Type: new Abstract: Long-term time series forecasting requires models that simultaneously capture rapid oscillations, medium-range periodicities, and slowly evolving macro-
arXiv:2605.01374v1 Announce Type: new Abstract: Knowledge distillation is a key technique for compressing large language models (LLMs), but most existing methods align representations at fixed layers
arXiv:2605.01369v1 Announce Type: cross Abstract: Deep learning has been widely adopted for WiFi CSI-based human activity recognition (HAR) due to its ability to learn spatio-temporal features in a pr
arXiv:2605.00885v1 Announce Type: new Abstract: Existing single image dehazing methods have demonstrated satisfactory performance on homogeneous thin-haze images; however, they often struggle with non
arXiv:2605.01563v1 Announce Type: new Abstract: We propose a unified cross-domain transfer learning framework that leverages knowledge from multiple heterogeneous medical imaging datasets to improve p
arXiv:2605.02871v1 Announce Type: cross Abstract: Composite materials exhibit strongly hierarchical and anisotropic properties governed by coupled mechanisms spanning constituents, plies, laminates, s
arXiv:2508.09193v2 Announce Type: replace Abstract: Recent advancements in generative modeling emphasize the importance of natural language as a highly expressive and accessible modality for controlli
arXiv:2605.01154v1 Announce Type: new Abstract: ARC-AGI-2 is a benchmark of human-intuitive visual puzzles that measures a machine's ability to generalize from limited examples, interpret symbolic mea
arXiv:2605.02437v1 Announce Type: new Abstract: Objective: Accurate probability estimates are essential for the safe deployment of medical image segmentation models in clinical decision-making. Howeve
arXiv:2605.01736v1 Announce Type: new Abstract: Understanding the geometric and semantic structure of environments is essential for embodied navigation and reasoning. Existing semantic mapping methods
arXiv:2605.01961v1 Announce Type: new Abstract: Learning from human preference data is becoming a useful tool, from fine-tuning large language models to training reinforcement learning agents. However
arXiv:2605.00872v1 Announce Type: cross Abstract: Hypertensive disorders of pregnancy remain a leading cause of maternal and fetal morbidity worldwide, yet diagnosis relies on intermittent cuff-based
arXiv:2605.01687v1 Announce Type: new Abstract: We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic
arXiv:2605.01219v1 Announce Type: cross Abstract: Audio-visual quality assessment (AVQA) is essential for streaming, teleconferencing, and immersive media. In realistic streaming scenarios, distortion
arXiv:2605.01163v1 Announce Type: cross Abstract: Shared embedding spaces are widely used for multimodal search and data curation. In practice, two problems often limit how well this works. First, emb
arXiv:2501.09775v3 Announce Type: replace Abstract: Multiple Choice Question (MCQ) tests are among the most used methods for evaluating large language models (LLMs). Besides checking the correctness o
arXiv:2605.02207v1 Announce Type: new Abstract: Pneumonia remains a leading global cause of morbidity and mortality, particularly in low resource settings where access to imaging, laboratory testing,
arXiv:2605.02471v1 Announce Type: new Abstract: Mapping standing dead trees is crucial for acquiring information on the effects of climate change on forests and forest biodiversity. However, leveragin
arXiv:2503.14505v3 Announce Type: replace Abstract: We introduce MusicInfuser, an approach that aligns pre-trained text-to-video diffusion models to generate high-quality dance videos synchronized wit
The Netherlands approved Tesla's Full Self-Driving (Supervised) system under UN Regulation 171 on April 10, 2026, becoming the first European country to do so. Other EU member states can recognize the
arXiv:2601.17756v3 Announce Type: replace Abstract: Existing Subject-to-Video Generation (S2V) methods have achieved high-fidelity and subject-consistent video generation, yet remain constrained to si
arXiv:2602.03668v2 Announce Type: replace-cross Abstract: Latent actions learned from diverse human videos serve as pseudo-labels for vision-language-action (VLA) pretraining, but provide effective su
my fav type of company - both pushing the cultural and technical frontier. @ylanrich has been obsessed with robotics restaurants for 10+ years - built a 5 fully-operational ones at 53% ebitda margin i
Ethan Mollick suggests that Mythos, likely an AI model or system, demonstrates strong capability in identifying and diagnosing pig diseases, possibly indicating its effectiveness in agricultural or ve
Chris Metinko / Axios: Nace.AI, which lets companies build specialized AI models tailored to their business' mission and language, raised a 21.5M seed led by Walden Catalyst — Nace.AI, which lets busi
arXiv:2605.00871v1 Announce Type: cross Abstract: State space models (SSMs) achieve linear-time complexity but struggle with multi-channel physiological signals due to three limitations: fixed kernels
arXiv:2511.03488v2 Announce Type: replace Abstract: Physiological signals are inherently heterogeneous: they are collected under diverse acquisition setups, differ in the number and type of modalities
arXiv:2605.02306v1 Announce Type: new Abstract: Bayesian filtering is a cornerstone of state estimation in complex systems such as aerospace systems, yet exact solutions are available only for linear
arXiv:2508.02046v4 Announce Type: replace-cross Abstract: Recent advances in Graphical User Interface (GUI) and embodied navigation have driven progress, yet these domains have largely evolved in isol
arXiv:2306.04498v3 Announce Type: replace Abstract: We study fair multi-agent multi-armed bandit learning under collision-only coordination. Agents cannot communicate explicitly during learning and ob
arXiv:2502.00204v3 Announce Type: replace Abstract: We study the problem of online learning in Stackelberg games with side information between a leader and a sequence of followers. In every round the
arXiv:2603.10584v2 Announce Type: replace Abstract: We introduce Marigold-SSD, a single-step, late-fusion depth completion framework that leverages strong diffusion priors while eliminating the costly
arXiv:2605.01075v1 Announce Type: new Abstract: Propagation-based X-ray phase-contrast imaging (PBI) enables high-contrast visualization of lung structures and holds strong medical potential. However,
arXiv:2605.01082v1 Announce Type: new Abstract: We study networked binary classification on a directed acyclic graph (DAG) where each agent observes only a subset of the feature columns of a shared da
arXiv:2605.02021v1 Announce Type: new Abstract: Autonomous spacecraft docking requires control policies that simultaneously ensure collision avoidance and target reachability under coupled, high-dimen
arXiv:2506.22899v3 Announce Type: replace Abstract: Neural Cellular Automata (NCAs) are bio-inspired dynamical systems in which identical cells iteratively apply a learned local update rule to self-or
arXiv:2605.02044v1 Announce Type: new Abstract: Training neural networks is difficult to interpret, particularly for newcomers. We introduce NeuroViz, an interactive visualization tool that supports r
arXiv:2605.01263v1 Announce Type: cross Abstract: We study query time bounds for the fundamental problem of estimating the kernel mean frac1{|X|}sum_{xin X}mathbf{k}(x,y) of a query y in a finite data
New from the LangSmith Signal: The vector space rapidly diversified since December. ✅ Managed cloud surged. MongoDB Atlas, Pinecone, + Qdrant tripled their combined share to 21%. ✅ Only 3 vector store
NEW paper from Microsoft Research. Nice study on long-horizon agent generalization. (bookmark it) The team runs a study where the only variable is task horizon length. They use the same decision rules
OpenAI introduced new advertising purchasing options for ChatGPT, expanding how businesses can buy ad placements within the platform. These new methods likely provide advertisers with additional flexi
arXiv:2605.01745v1 Announce Type: cross Abstract: Language data are increasingly acquired and governed as assets, yet platforms often price candidate resources before knowing their true privacy or acc
Ollama not using GPU is commonly diagnosed by running `ollama ps`—if it shows 100% CPU, Ollama isn't detecting the GPU. The issue typically has multiple causes, with common ones including driver probl
arXiv:2510.23633v2 Announce Type: replace-cross Abstract: Pretrained diffusion models have demonstrated strong capabilities in zero-shot inverse problem solving by incorporating observation informatio