Knowledge catalogue
@jon_barron 'World models' has a technical meaning - the transition model/dynamics model from Bellman/Kalman in the context of MDPs/ state space approach to control theory ~ 1960. I gave a talk on thi
arXiv:2604.24031v1 Announce Type: new Abstract: The encoder-decoder framework has become widely popular nowadays. In this model, the encoder extracts informative visual features from an input image, a
arXiv:2604.23478v1 Announce Type: new Abstract: Large language models are increasingly deployed as automated judges for evaluating other models, yet the stability of their verdicts under semantically
arXiv:2604.23178v1 Announce Type: new Abstract: LLM-as-a-Judge has become the dominant paradigm for evaluating language model outputs, yet LLM judges exhibit systematic biases that compromise evaluati
Just received new reach minis for the Miami office! This is the first robot that goes out to people with agentic software meaning anyone can build any apps with their agents so excited to see what peo
arXiv:2604.24645v1 Announce Type: cross Abstract: The development of practical (multimodal) large language model assistants for Korean weather forecasters is hindered by the absence of a multidimensio
arXiv:2604.23056v1 Announce Type: cross Abstract: We propose a simple yet effective alternative to reward normalization in policy gradient reinforcement learning by integrating a 1D Kalman filter for
arXiv:2604.23493v1 Announce Type: cross Abstract: Early detection of mental health conditions, particularly stress and depression, from social media text remains a challenging open problem in computat
arXiv:2604.23320v1 Announce Type: new Abstract: The Convolutional Neural Networks (CNNs) have been the dominant and effective approach for general computer vision tasks. Recently, Kolmogorov-Arnold ne
arXiv:2604.22779v1 Announce Type: cross Abstract: Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucination
This post describes a project where the author leveraged Andrej Karpathy's compact GPT implementation to create a tool for converting pandas DataFrames into searchable context windows, which they then
arXiv:2603.01581v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models build a token-domain robot control paradigm, yet suffer from low speed. Speculative Decoding (SD) is an op
arXiv:2604.23387v1 Announce Type: new Abstract: Accurate 6-DoF pose estimation of objects is critical for robots to perform precise manipulation tasks. However, for dynamic object pose estimation, con
arXiv:2602.17547v3 Announce Type: replace Abstract: This paper introduces KLong, an open-source LLM agent trained to solve extremely long-horizon tasks. The principle is to first cold-start the model
arXiv:2604.23435v1 Announce Type: cross Abstract: Radiographic grading of knee osteoarthritis (KOA) with the Kellgren-Lawrence (KL) system is limited by inter-reader variability and the opacity of cur
arXiv:2604.23257v1 Announce Type: cross Abstract: Software engineering (SE) organizations operate in a knowledge-intensive domain where critical assets -- architectural expertise, design rationale, an
arXiv:2604.23877v1 Announce Type: new Abstract: Logical reasoning serve as a central capability in LLMs and includes three main forms: deductive, inductive, and abductive reasoning. In this work, we s
arXiv:2604.23948v1 Announce Type: cross Abstract: The Korean writing system, extit{Hangeul}, has a unique character representation rigidly following the invention principles recorded in extit{Hunminje
Alice Hancock / Financial Times: Kpler, an online analytics platform tracking global maritime traffic and energy flows, says it has gained millions of new users since the war in Iran began — Kpler rep
arXiv:2604.24432v1 Announce Type: cross Abstract: Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic unde
Large Language Models (LLMs) demonstrate their reasoning ability through chain-of-thought (CoT) generation. However, LLM’s autoregressive decoding may limit the ability to revisit and refine earlier t
arXiv:2505.11772v3 Announce Type: replace Abstract: We introduce LAMP (Local Attribution Mapping Probe), a method that shines light onto a black-box language model's decision surface and studies how r
arXiv:2506.19089v5 Announce Type: replace-cross Abstract: We introduce StorySim, a programmable framework for synthetically generating stories to evaluate the theory of mind (ToM) and world modeling (
arXiv:2604.23513v1 Announce Type: new Abstract: In high-conflict mixed-traffic scenarios involving human-driven and autonomous vehicles, most existing autonomous driving systems default to overly cons
arXiv:2604.22938v1 Announce Type: cross Abstract: The promise of data-driven materials discovery remains constrained by the scarcity of large, high-quality, and accessible experimental datasets. Here,
arXiv:2509.06337v2 Announce Type: replace Abstract: Questionnaire-based surveys are foundational to social science research and public policymaking, yet traditional survey methods remain costly, time-
arXiv:2604.24110v1 Announce Type: cross Abstract: Multi-agent LLM tutoring systems improve response quality through agent specialization, but each student query triggers several concurrent API calls w
arXiv:2604.24293v1 Announce Type: cross Abstract: Graph neural ordinary differential equations (Graph ODEs) extend graph learning from discrete message-passing layers to continuous-time representation
arXiv:2604.23858v1 Announce Type: new Abstract: Video generation, while capable of generating realistic videos, is computationally expensive and slow, prohibiting real-time applications. In this paper
arXiv:2604.23268v1 Announce Type: new Abstract: This paper introduces a novel multi frame super-resolution network (MFSR) for burst hexadeca Bayer pattern Contact Image Sensor (CIS) images, which incl
arXiv:2505.12009v2 Announce Type: replace Abstract: Expressive human pose and shape estimation (EHPS) plays a central role in digital human generation, particularly in live-streaming applications. How
arXiv:2511.21213v2 Announce Type: replace-cross Abstract: Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, ZT. To accelerate the dis
arXiv:2604.23957v1 Announce Type: new Abstract: Proactive watermarking offers a promising approach for deepfake tamper detection and localization in short-form videos. However, existing methods often
arXiv:2604.23324v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have demonstrated impressive performance in learning representations from graph-structured data. However, their message-p
arXiv:2604.24542v1 Announce Type: cross Abstract: Large language models deployed at runtime can misbehave in ways that clean-data validation cannot anticipate: training-time backdoors lie dormant unti
This resource explains techniques for creating videos with consistent characters and voices in Runway, likely covering the use of reference materials, character sheets, and specific prompting strategi
This resource provides instructions for setting up and running a local coding agent using LM Studio's serving engine, featuring the Pi agent framework and Google's Gemma 4 26B language model. It demon
Mistral AI announced new workflow capabilities or features, likely detailing how users can implement multi-step processes or automation using their AI models and services. The announcement was shared
arXiv:2506.11480v4 Announce Type: replace-cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a key technique for enhancing LLMs' reasoning abilities, yet its data ineffic
arXiv:2604.23403v1 Announce Type: cross Abstract: This paper proposes a new method to improve the training efficiency of deep convolutional neural networks. During training, the method evaluates score
arXiv:2510.14978v2 Announce Type: replace Abstract: Recent image editing models have achieved impressive results while following natural language editing instructions, but they rely on supervised fine
arXiv:2410.01580v3 Announce Type: replace Abstract: Algorithmic recourse provides individuals who receive undesirable outcomes from machine learning systems with minimum-cost improvements to achieve a
arXiv:2508.19068v2 Announce Type: replace Abstract: Single-Pixel Imaging (SPI) enables the reconstruction of objects using a single detector through sequential illuminations with structured light patt
arXiv:2604.23212v1 Announce Type: cross Abstract: Existing large-dimensional theory for spectral algorithms resolves either the optimally tuned point or the interpolation limit, but leaves the under-r
arXiv:2604.24376v1 Announce Type: new Abstract: Depression places substantial pressure on mental health services, and many people describe their experiences outside clinical settings in high-volume us
arXiv:2604.23360v1 Announce Type: new Abstract: Learning from demonstration is widely used for robot navigation, yet it suffers from a fundamental limitation: demonstrations consist predominantly of s
arXiv:2604.23125v1 Announce Type: new Abstract: Real-world data often exhibit long-tailed distributions with numerous noisy labels, substantially degrading the performance of deep models. While prior
arXiv:2604.23314v1 Announce Type: new Abstract: Segmentation is central to clinical diagnosis and monitoring, yet the reliability of modern foundation models in medical imaging still depends on the av
arXiv:2604.23000v1 Announce Type: new Abstract: In behavioral cloning (BC), policy performance is fundamentally limited by demonstration data quality. Real-world datasets contain trajectories of varyi
arXiv:2209.14742v2 Announce Type: replace Abstract: To address distribution shifts between training and test data, domain generalization (DG) leverages multiple source domains to learn a model that ge
arXiv:2604.24681v1 Announce Type: new Abstract: Human videos contain rich manipulation priors, but using them for robot learning remains difficult because raw observations entangle scene understanding
arXiv:2604.22770v1 Announce Type: cross Abstract: Most digital language learning curricula rely on discrete-item quizzes that test recall rather than applied conversational proficiency. When progressi
arXiv:2604.23867v1 Announce Type: new Abstract: Scientific measurements are often bottlenecked by suboptimal conditions, whether that be noise, incomplete spatial coverage, or limited resolution, rend
arXiv:2507.20088v3 Announce Type: replace Abstract: We study neural architectures in which each hidden layer is defined by the stationary state of a dissipative Schrodinger-type dynamics on a learned
arXiv:2504.18184v4 Announce Type: replace-cross Abstract: We consider a class of statistical inverse problems involving the estimation of a regression operator from a Polish space to a separable Hilbe
arXiv:2503.20066v2 Announce Type: replace-cross Abstract: Dense reconstruction and differentiable rendering are fundamental tightly connected operations in 3D vision and computer graphics. Recent neur
arXiv:2604.23855v1 Announce Type: new Abstract: We present a deployed system that automates end-to-end customer support workflows inside an enterprise Business Process Management (BPM) platform. The a
arXiv:2509.10546v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most r
arXiv:2604.23683v1 Announce Type: new Abstract: Historical encrypted manuscripts require both paleographic interpretation of cipher symbols and cryptanalytic recovery of plaintext. Most existing compu
arXiv:2604.23604v1 Announce Type: new Abstract: Understanding the surrounding environment is fundamental in autonomous driving and robotic perception. Distinguishing between known classes and previous