Knowledge catalogue
arXiv:2609.04710v1 Announce Type: cross Abstract: Inferring cellular dynamics from unpaired single-cell snapshots requires modeling both state transitions and population growth or death. Unbalanced dy
arXiv:2609.05125v1 Announce Type: new Abstract: Evaluating the calibration of Large Language Models (LLMs) is critical for their safe deployment as zero-shot classifiers. Yet, commercial API providers
arXiv:2609.04639v1 Announce Type: new Abstract: Symbolic regression (SR) discovers closed-form mathematical expressions from data, offering interpretability beyond black-box models. Existing methods s
arXiv:2609.05174v1 Announce Type: new Abstract: Explainability is increasingly seen as a crucial requirement in AI-based medical diagnosis, particularly in safety-critical clinical decision-making. Mo
arXiv:2603.20686v2 Announce Type: replace-cross Abstract: Recent advancements in text-to-speech technologies enable generating high-fidelity synthetic speech nearly indistinguishable from real human v
arXiv:2606.17398v2 Announce Type: replace-cross Abstract: Binary reversing is fundamental to software understanding, vulnerability discovery, malware investigation, and firmware auditing. However, it
arXiv:2609.04902v1 Announce Type: cross Abstract: Can we recover the 3D poses of multiple people using only sound? This paper presents the first attempt to estimate multi-person 3D poses solely from a
arXiv:2609.04282v1 Announce Type: new Abstract: Diffusion models have become the mainstream paradigm for modern visual generation and have substantially advanced multimedia content synthesis, especial
arXiv:2609.05335v1 Announce Type: cross Abstract: Public vulnerability databases collect rich information about known software flaws, including their weakness types, affected components, and related p
arXiv:2609.04325v1 Announce Type: new Abstract: We explore the use of simulated data for training a model for protein annotation in crowded cryo-electron tomography volumes reconstructed from images c
I've hit again a point where me as a developer have to take a break from all this slop shit. Im a Developer for 13+ years and i loved it. But i fell for the slop trap. First it started with copilot an
arXiv:2609.05388v1 Announce Type: new Abstract: Visual reasoning tasks require a system to jointly perceive visual content and apply formal relational constraints---a combination that neither pure neu
arXiv:2603.27520v2 Announce Type: replace Abstract: In video diffusion transformers, visual patch tokens maintain explicit correspondence to space and time. We hypothesize that their channel dimension
arXiv:2609.04911v1 Announce Type: new Abstract: Interactive visual world models must distinguish observation from physical intervention. Camera motion reveals new surfaces, whereas intervention change
arXiv:2508.06207v3 Announce Type: replace Abstract: Back-support exoskeletons mitigate musculoskeletal strain, yet current systems rely on reactive sensing and lack context-aware assistance modulation
arXiv:2503.08904v3 Announce Type: replace Abstract: The recent developments in data-driven methods have paved the way to new methodologies to provide accurate state reconstruction of engineering syste
arXiv:2609.05369v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon procedures requiring persistent task sta
arXiv:2609.05261v1 Announce Type: new Abstract: Large language model agents increasingly rely on execution traces to master complex interactive tasks. However, current paradigms are bottlenecked by sh
arXiv:2609.04678v1 Announce Type: new Abstract: Existing post-training pipelines for coding and terminal agents suffer severe token and control fidelity errors: simplified training environments mismat
arXiv:2609.05091v1 Announce Type: new Abstract: Industrial anomaly detection must handle two distinct defect families: structural anomalies, which manifest as local texture corruptions, and logical an
arXiv:2609.04242v1 Announce Type: cross Abstract: Audio-visual understanding remains challenging because models must jointly interpret spoken content, visual events, and their temporal relationships.
arXiv:2609.04365v1 Announce Type: cross Abstract: Decompensation represents a critical transition in the course of cirrhosis, yet clinicians have limited non-invasive tools to reliably predict its ons
arXiv:2609.04948v1 Announce Type: cross Abstract: Multi-expert models have become the dominant paradigm for long-tailed learning, largely attributed to their presumed ability to benefit from expert di
arXiv:2609.04355v1 Announce Type: cross Abstract: Pretrained vision-language-action (VLA) models enable broad manipulation but remain unreliable in tasks demanding precision and repeatability. Applyin
arXiv:2607.10749v2 Announce Type: replace Abstract: Reflections of water pose a significant challenge for computer vision systems, as standard deep learning models frequently confuse objects with thei
arXiv:2510.11839v3 Announce Type: replace Abstract: Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, au
arXiv:2505.18686v3 Announce Type: replace Abstract: Weakly supervised referring expression comprehension(WREC) and segmentation(WRES) aim to learn object grounding based on a given expression using we
arXiv:2609.05405v1 Announce Type: new Abstract: Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whethe
arXiv:2609.04827v1 Announce Type: new Abstract: Monocular depth estimation foundation models, such as the Depth Anything series, have achieved remarkable performance across diverse domains. However, t
arXiv:2609.04741v1 Announce Type: new Abstract: Recent zero-shot 3D visual grounding methods leverage vision-language models (VLMs) to localize objects in 3D scenes from natural language queries. Howe
arXiv:2609.04373v1 Announce Type: new Abstract: Large language models (LLMs) are being deployed at scale in consequential real-world systems, from financial markets to content moderation to hiring. We
arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the
arXiv:2609.04707v1 Announce Type: cross Abstract: Wireless foundation models (WFMs) have emerged as a promising approach for learning reusable representations from large-scale wireless data and adapti
Right, so this is going to be embarrassing but it's presumably something we've all been through at one point or another, and I guess this is my first time resolving something like this in the way that
https://village-sim-one.vercel.app/ - 16GB VRAM RTX 5070 Ti, fully offloaded - Vision on CPU - Windows, not headless - beellama.cpp - latest version with the kvarn performance enhancements making it a
How we think about the “wiki incident,” where our agents wrote to several internet sites: it’s past time for us to define standards for when and how we share misalignment incidents, not just misalignm
This is a weird behavior in coding models and something worth looking into. It turns that some models over-edit code that another models wrote. There is a high chance that your repo now has commits fr
arXiv:2609.03621v1 Announce Type: new Abstract: Making science computable requires representations of both scientific knowledge and the physical world in which scientific claims are tested. A computab
arXiv:2609.03457v1 Announce Type: new Abstract: Accurate cloud resource forecasting is essential for proactive resource provisioning, maintaining Quality of Service (QoS), and reducing operational cos
arXiv:2609.03355v1 Announce Type: cross Abstract: Logit-based knowledge distillation for autoregressive language models usually aligns teacher and student next-token distributions over the entire voca
arXiv:2609.03258v1 Announce Type: new Abstract: Parking spot classification is a fundamental task in intelligent transportation systems, yet most deep learning approaches rely on large amounts of anno
arXiv:2511.15884v2 Announce Type: replace-cross Abstract: Recovering the 9D pose of objects, both their 6D pose and 3D dimensions, under clutter and occlusion is a core requirement for warehouse autom
arXiv:2609.03668v1 Announce Type: new Abstract: Accurate segmentation of corneal layers in optical coherence tomography (OCT) is essential for quantitative assessment of corneal morphology, including
arXiv:2607.15565v2 Announce Type: replace-cross Abstract: Where should the question go in a vision-language model (VLM) prompt: before the image or after it? Intuition says before: knowing what is ask
arXiv:2609.03239v1 Announce Type: new Abstract: In the one-time selling B2B context, the buying cycle may last months or even years. During the long process, targeting customers that have a high poten
arXiv:2609.04120v1 Announce Type: new Abstract: Video virtual try-on (VVT) aims to generate realistic videos of a person wearing a target garment. Recent methods leverage a keyframe-driven video gener
arXiv:2609.03502v1 Announce Type: cross Abstract: In low-resource settings, deploying TTS typically requires choosing between a large voice-cloning model with costly inference or a compact fixed-voice
arXiv:2609.03675v1 Announce Type: new Abstract: Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency con
arXiv:2602.00266v2 Announce Type: replace Abstract: Two deep ReLU networks can have entirely different architectures and parameters, yet realize the same function. We provide a complete characterizati
arXiv:2609.04070v1 Announce Type: new Abstract: Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a
arXiv:2609.02892v1 Announce Type: cross Abstract: Single-turn code-generation metrics understate a central property of deployed agents: whether they can repair a wrong artifact after receiving concret
arXiv:2609.03190v1 Announce Type: cross Abstract: Many biomedical challenges can be posed as tensor completion problems where the observed entries of a multidimensional array (a tensor) are used to im
arXiv:2609.03107v1 Announce Type: cross Abstract: Recent advances in generative speech models have made it increasingly difficult to distinguish authentic from synthetic audio, enabling new forms of f
arXiv:2609.03894v1 Announce Type: new Abstract: Large language models (LLMs) have become ubiquitous tools for code generation and editing. However, development teams often use multiple LLM assistants.
arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo
arXiv:2310.20096v2 Announce Type: replace-cross Abstract: The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expect
arXiv:2609.03787v1 Announce Type: new Abstract: AI agents increasingly gather evidence, invoke tools, apply constraints, and produce decisions that people or software may commit to action. A final out
arXiv:2609.03438v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are increasingly used to execute natural-language instructions on user interfaces, yet real users may issue infeas
arXiv:2609.03572v1 Announce Type: new Abstract: World models offer a promising paradigm for autonomous driving by predicting how traffic scenes may evolve and using such predictions to support action
arXiv:2609.04031v1 Announce Type: new Abstract: Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practi