Knowledge catalogue
arXiv:2609.21320v1 Announce Type: cross Abstract: Modern text and image representations are often matrix-valued, with rows corresponding to tokens, patches, or other local feature vectors. Predictive
arXiv:2609.22008v1 Announce Type: cross Abstract: Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit de
arXiv:2609.21698v1 Announce Type: new Abstract: Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive
arXiv:2609.21138v1 Announce Type: cross Abstract: Octopus crawling motivates soft robots that exploit redundancy, yet discovering and organizing diverse coordination modes for adaptation remains chall
arXiv:2609.21857v1 Announce Type: cross Abstract: LLMs are increasingly used in social simulations for socially interactive agents and robots, offering more flexibility than rule-based systems. Howeve
arXiv:2609.20912v1 Announce Type: new Abstract: In this work, we study the neural scaling laws of RydbergGPT, an autoregressive transformer model trained on qubit projective measurement data gathered
arXiv:2609.20824v1 Announce Type: new Abstract: We explore whether entropy-based confidence signals can be leveraged to improve the accuracy of Small Language Models (SLMs) with fewer than 3 billion p
arXiv:2609.21000v1 Announce Type: cross Abstract: Spinning frequency-modulated continuous-wave (FMCW) radars have been gaining popularity in autonomous vehicle perception on account of their robustnes
Document classification and splitting idea using @typesafeai Jev based on LiteParse, and LlamaParse. Classify: categorize probabilities, and review flags. Measure: separate OCR and decision timing, pr
arXiv:2609.21504v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) has advanced rapidly in static indoor environments, but robots operating in human-populated spaces must ground lang
arXiv:2609.21486v1 Announce Type: new Abstract: Multimodal trajectory prediction improves behavioral coverage in end-to-end autonomous driving, but existing methods remain limited by sparse scene repr
arXiv:2609.21675v1 Announce Type: new Abstract: Despite the remarkable progress in Multimodal Large Language Models (MLLMs), prevailing Chain-of-Thought (CoT) paradigms remain confined to the natural-
arXiv:2412.07151v1 Announce Type: cross Abstract: Distributed model training needs to be adapted to challenges such as the straggler effect and Byzantine attacks. When coordinating the training proces
arXiv:2609.21548v1 Announce Type: new Abstract: Sequential recommendation aims to predict the next item a user will interact with based on their historical behavior. Advances in Transformers have sign
arXiv:2609.22073v1 Announce Type: new Abstract: Quadrupedal robots are increasingly deployed in environments where locomotion must remain robust to disturbances and constrained terrain. Gait type, suc
arXiv:2609.05799v2 Announce Type: replace Abstract: In streaming simultaneous speech translation, the speech translation system is trained to learn a read-write policy that alternates between consumin
arXiv:2609.21099v1 Announce Type: new Abstract: Coaxial rotor drones have generated considerable interest because of energy efficiency and small size, but they are afflicted with inherent underactuati
arXiv:2609.21100v1 Announce Type: new Abstract: Learning in robotic games is constrained not only by strategic information but also by what the body can still execute. We study this coupling in a hier
arXiv:2510.13046v3 Announce Type: replace Abstract: State space models offer linear-time sequence modeling and are a promising backbone for multi-label 12-lead ECG classification, but the design choic
arXiv:2609.21755v1 Announce Type: new Abstract: Emergency department (ED) decision-making relies on heterogeneous clinical information, including patient history, vital signs, laboratory results, and
arXiv:2609.21268v1 Announce Type: new Abstract: Text-guided video editing modifies target content while preserving the appearance and temporal coherence of unedited regions. Training-based approaches
arXiv:2609.21457v1 Announce Type: new Abstract: Deep neural architectures are widely used for signal processing in automated pain assessment systems. However, architecture design has remained largely
arXiv:2609.20954v1 Announce Type: new Abstract: We present a novel end-to-end model-based Reinforcement Learning (RL) algorithm for efficient policy synthesis under given Linear Temporal Logic (LTL) s
arXiv:2609.21267v1 Announce Type: new Abstract: Production LLM agents are evaluated repeatedly as they evolve, but full agent benchmarks are costly to rerun. We study efficient recurring evaluation fo
arXiv:2602.18071v2 Announce Type: replace Abstract: Humans rearrange objects in cluttered environments using egocentric perception, actively moving to keep task-relevant spatial cues in view. Mobile r
arXiv:2609.20888v1 Announce Type: new Abstract: Massive KV caches can cause severe memory-bandwidth bottlenecks during long-context decoding. Sparse attention methods mitigate this via selective loadi
arXiv:2609.21941v1 Announce Type: cross Abstract: The importance of deep neural networks (DNNs) is widely recognized, and the parameters obtained through training are regarded as valuable assets. Rece
arXiv:2609.20849v1 Announce Type: new Abstract: Large Audio Language Models (LALMs) perform well on complex question answering but often show a reasoning gap, where explicit Chain-of-Thought (CoT) red
arXiv:2609.21151v1 Announce Type: cross Abstract: Molecular solubility directly affects key aspects of molecular development such as reaction feasibility, formulation performance, separation efficienc
arXiv:2609.21841v1 Announce Type: new Abstract: Frontier language models now produce professional deliverables that expert graders judge to match human work on a substantial share of economically valu
arXiv:2609.21595v1 Announce Type: new Abstract: In-context learning using Large Language Models (LLMs) offers a compelling path to training-free post-OCR correction, yet its effectiveness for Devanaga
arXiv:2603.05807v2 Announce Type: replace Abstract: Event cameras are rapidly rising in popularity for robotic and computer vision tasks because their sparse activation delivers energy-efficient, high
arXiv:2609.21899v1 Announce Type: new Abstract: Best-of-n (BoN) sampling is a simple yet effective inference-time alignment method, but hard maximization provides only coarse control over the trade-of
arXiv:2601.06848v2 Announce Type: replace Abstract: Multimodal aspect-based sentiment analysis (MABSA) aims to identify aspect-level sentiments by jointly modeling textual and visual information, whic
arXiv:2609.21629v1 Announce Type: new Abstract: Multi-Channel imaging (MCI) data differs fundamentally from natural images, as each channel records a semantically distinct signal rather than a colour
arXiv:2609.20897v1 Announce Type: cross Abstract: We study a minimal classification problem: Given independent labeled observations Xsim P and Zsim Q from two unknown distributions P,Q, and given an i
arXiv:2509.25252v3 Announce Type: replace Abstract: 'The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge.' Large Language Models have conquered natural language but remai
arXiv:2609.21296v1 Announce Type: cross Abstract: Fairness research on language models involves measuring bias, applying mitigation methods, and examining the evidence on which an evaluation rests. Ex
arXiv:2609.21358v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models pre-trained on large-scale, closed datasets have demonstrated remarkable success across diverse robotic manipulation
arXiv:2609.21306v1 Announce Type: new Abstract: A common requirement across organizations is to have a tool that can identify file types based on their contents, particularly in the cybersecurity doma
arXiv:2603.17201v2 Announce Type: replace Abstract: Visual SLAM systems combine visual tracking with global loop closure to maintain a consistent map and accurate localization. Loop closure is a compu
arXiv:2609.21057v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training without sharing raw data, but its performance degrades under non-IID data and stochastic cl
arXiv:2609.21829v1 Announce Type: cross Abstract: Clustering high-dimensional data is a fundamental task in unsupervised machine learning with applications to a variety of domains. In the centralized
arXiv:2609.21216v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies based on flow matching generate action chunks through repeated evaluations of an action expert. Increasing the n
arXiv:2609.21354v1 Announce Type: new Abstract: High-speed tracking of small, fast-moving organisms in their natural environments is important to better understand their behavior and ecology. Traditio
Finally, a company brain that actually works! Codos starts with the people doing the work. It interviews employees to find which tasks can be automated, then deploys the automations and keeps learning
arXiv:2609.21228v1 Announce Type: cross Abstract: Vision-language-action (VLA) models built on pretrained vision-language models have demonstrated strong performance across diverse robotic manipulatio
arXiv:2609.21447v1 Announce Type: cross Abstract: Humanoid locomotion over complex terrain requires anticipating footholds that may no longer be visible at touchdown. Limited camera coverage and self-
On September 21 2026, Yohei reported results from a hard “insect‑identification” benchmark where model accuracy spanned 23 points across the evaluated systems. The Qwen 4B + Glance model scored 0.96,
arXiv:2609.21751v1 Announce Type: cross Abstract: Manipulating objects requires understanding not only their motion, but also the physical properties that determine it. For articulated objects, these
arXiv:2609.20980v1 Announce Type: new Abstract: Vision-language-action (VLA) models have demonstrated strong capabilities in robotic manipulation, yet their reliance on visual perception limits robust
arXiv:2609.21497v1 Announce Type: new Abstract: Effective physical interaction control in robotic manipulation requires not only kinematically feasible motion but also sufficient force-interaction cap
Found a great production use case for Jev. I used Jev to organize ~2.3K AI research papers. The total cost was $0.14, and it took about 83 seconds. The process: The papers already had old tags, which
arXiv:2609.21012v1 Announce Type: new Abstract: Artistic style classification is usually studied on complete artworks, where models can exploit global composition, spatial organisation, and iconograph
Free SemIf this week is useful. Typed outputs + probabilities look like a cleaner way to route agents than parsing LLM text every time. jev is a new type of model - 'decision models' there are a few o
arXiv:2609.21667v1 Announce Type: cross Abstract: Software is a first-class scientific object, yet validated links between source code and the scholarly record remain largely absent from the Linked Op
arXiv:2609.20827v1 Announce Type: new Abstract: Hospital discharge education is an interactive teaching task: a clinician adapts a discharge plan to a patient's literacy, recall, and personality. Exis
Today, Egypt’s AI builders gathered in the Grand Egyptian Museum for a reception that highlighted the nation’s rapidly growing AI ecosystem — spanning AI natives, developers, researchers, startups and
arXiv:2609.20838v1 Announce Type: new Abstract: In this study, we examine how modern LLMs generate and detect fake news under controlled settings across four manipulation scenarios. These are open-end
arXiv:2609.21349v1 Announce Type: cross Abstract: Large language models have shown strong potential as role-playing agents for real individuals, yet faithful impersonating remains challenging. Existin