Knowledge catalogue
arXiv:2604.03753v2 Announce Type: replace-cross Abstract: Modern advanced driver assistance systems (ADAS) rely on deep neural networks (DNNs) for perception and planning. Since DNNs' parameters resid
arXiv:2602.00793v2 Announce Type: replace-cross Abstract: Speaking aloud to a wearable AR assistant in public can be socially awkward, and re-articulating the same requests every day creates unnecessa
arXiv:2604.09737v1 Announce Type: cross Abstract: Structured prediction requires models to generate ontology-constrained labels, grounded evidence, and valid structure under ambiguity, label skew, and
arXiv:2601.15671v2 Announce Type: replace-cross Abstract: Designing cycling infrastructure requires balancing the competing needs of diverse user groups, yet designers often struggle to anticipate how
arXiv:2604.10516v1 Announce Type: new Abstract: Selecting the right knowledge is critical when using large language models (LLMs) to solve domain-specific data analysis tasks. However, most retrieval-
arXiv:2501.07773v3 Announce Type: replace Abstract: Generative modeling of symmetric densities has a range of applications in AI for science, from drug discovery to physics simulations. The existing g
arXiv:2511.06101v3 Announce Type: replace-cross Abstract: Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored
arXiv:2604.11563v1 Announce Type: cross Abstract: Providing AI agents with reliable long-term memory that does not hallucinate remains an open problem. Current approaches to memory for LLM agents -- s
arXiv:2604.11498v1 Announce Type: new Abstract: Fine-grained human action recognition (FHAR) is challenging because visually similar actions differ by subtle spatio-temporal cues. Many recent systems
arXiv:2509.04123v2 Announce Type: replace Abstract: Text-to-story visualization is challenging due to the need for consistent interaction among multiple characters across frames. Existing methods stru
arXiv:2604.10720v1 Announce Type: new Abstract: Artificial models that simulate how learners act and respond within educational systems are a promising tool for evaluating tutoring strategies and feed
arXiv:2604.10577v1 Announce Type: cross Abstract: Computer-use agents (CUAs) can now autonomously complete complex tasks in real digital environments, but when misled, they can also be used to automat
This appears to be a brief, informal reply post on X (formerly Twitter) directed at user @themaxburns, made in response to a conversation involving Yann LeCun, a prominent AI researcher and Chief AI S
arXiv:2604.10458v1 Announce Type: cross Abstract: Wearable IMU-based Human Activity Recognition (HAR) relies heavily on Deep Neural Networks (DNNs), which are burdened by immense computational and buf
arXiv:2604.11193v1 Announce Type: new Abstract: Multi-hop Knowledge Graph Question Answering (KGQA) requires coherent reasoning across relational paths, yet existing methods often treat each reasoning
arXiv:2604.09648v1 Announce Type: new Abstract: Quantifying exhaled CO2 from free-roaming cattle is both a direct indicator of rumen metabolic state and a prerequisite for farm-scale carbon accounting
arXiv:2604.10721v1 Announce Type: cross Abstract: Natural-language Guided Cross-view Geo-localization (NGCG) aims to retrieve geo-tagged satellite imagery using textual descriptions of ground scenes.
arXiv:2512.17270v2 Announce Type: replace-cross Abstract: Role-playing models (RPMs) are widely used in real-world applications but underperform when deployed in the wild. This degradation can be attr
arXiv:2603.08715v2 Announce Type: replace-cross Abstract: Rapid advances in language models (LMs) have created new opportunities for automated code generation while complicating trade-offs between mod
arXiv:2604.11671v1 Announce Type: cross Abstract: Accurate material recognition is a fundamental capability for intelligent perception systems to interact safely and effectively with the physical worl
arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim
arXiv:2604.10022v1 Announce Type: new Abstract: Weird generalization is a phenomenon in which models fine-tuned on data from a narrow domain (e.g. insecure code) develop surprising traits that manifes
We've been working on this for a while. Can't wait to hear what you think We've redesigned Claude Code on desktop. You can now run multiple Claude sessions side by side from one window, with a new sid
arXiv:2601.06165v2 Announce Type: replace-cross Abstract: Current vision-language benchmarks predominantly feature well-structured questions with clear, explicit prompts. However, real user queries ar
arXiv:2510.26202v2 Announce Type: replace-cross Abstract: Human feedback can alter language models in unpredictable and undesirable ways, as practitioners lack a clear understanding of what feedback d
arXiv:2604.02458v2 Announce Type: replace-cross Abstract: Behavioral simulation is increasingly used to anticipate responses to interventions. Large language models (LLMs) enable researchers to specif
arXiv:2604.10990v1 Announce Type: cross Abstract: Scientific claim verification, the task of determining whether claims are entailed by scientific evidence, is fundamental to establishing discoveries
arXiv:2604.11809v1 Announce Type: new Abstract: Finding matching keypoints between images is a core problem in 3D computer vision. However, modern matchers struggle with large in-plane rotations. A st
arXiv:2604.10898v1 Announce Type: new Abstract: Large language models (LLMs) have shown great performance on complex reasoning tasks but often require generating long intermediate thoughts before reac
arXiv:2604.08645v1 Announce Type: cross Abstract: Large multimodal models are increasingly used as the reasoning core of embodied agents operating in 3D environments, yet they remain prone to hallucin
arXiv:2604.09157v1 Announce Type: cross Abstract: We introduce a novel learning framework for accelerated Monte Carlo (MC) dose calculation termed Energy-Shifting. This approach leverages deep learnin
arXiv:2604.03512v2 Announce Type: replace Abstract: Outage management in large-scale cloud operations remains heavily manual, requiring rapid triage, cross-team coordination, and experience-driven dec
arXiv:2604.05529v2 Announce Type: replace Abstract: Human mobility modeling is indispensable for diverse urban applications. However, existing data-driven methods often suffer from data scarcity, limi
arXiv:2604.08893v1 Announce Type: cross Abstract: Glioma is a harmful brain tumor that requires early detection to ensure better health results. Early detection of this tumor is key for effective trea
arXiv:2604.09462v1 Announce Type: new Abstract: Assistive teleoperation enhances efficiency via shared control, yet inter-operator variability, stemming from diverse habits and expertise, induces high
arXiv:2604.08866v1 Announce Type: cross Abstract: As organizations increasingly deploy AI as a teammate rather than a standalone tool, morally consequential mistakes often arise from joint human-AI wo
arXiv:2604.08963v1 Announce Type: cross Abstract: While Multi-Agent Systems (MAS) are increasingly deployed for complex workflows, their emergent properties-particularly the accumulation of bias-remai
arXiv:2604.09451v1 Announce Type: cross Abstract: The accelerometer has become an almost ubiquitous device, providing enormous opportunities in healthcare monitoring beyond step counting or other aver
A Reddit post from r/ChatGPT humorously describes a user's experience of ChatGPT's voice model abruptly ending a conversation in response to 'your mom' jokes, with the user then comically lamenting be
arXiv:2604.09288v1 Announce Type: new Abstract: Trusted multi-view classification typically relies on a view-wise evidential fusion process: each view independently produces class evidence and uncerta
arXiv:2509.16606v5 Announce Type: replace-cross Abstract: In networked multi-agent reinforcement learning (Networked-MARL), decentralized agents must act under local observability and constrained comm
arXiv:2604.09414v1 Announce Type: cross Abstract: Learning-to-Defer routes each input to the expert that minimizes expected cost, but it assumes that the information available to every expert is fixed
arXiv:2604.09537v1 Announce Type: cross Abstract: Evidence-grounded reasoning requires more than attaching retrieved text to a prediction: a model should make decisions that depend on whether the prov
arXiv:2603.18561v2 Announce Type: replace Abstract: Planning-oriented end-to-end driving models show great promise, yet they fundamentally learn statistical correlations instead of true causal relatio
arXiv:2604.08772v1 Announce Type: cross Abstract: Atmospheric clouds exhibit complex three-dimensional structure and microphysical details that are poorly constrained by the predominantly two-dimensio
arXiv:2503.00035v2 Announce Type: replace-cross Abstract: Large language models (LLMs) struggle with hallucinations due to false or outdated knowledge. Given the high resource demands of retraining th
arXiv:2510.21588v2 Announce Type: replace-cross Abstract: Biological and artificial learners are inherently exposed to a stream of data and experience throughout their lifetimes and must constantly ad
Vercel has introduced a 'Copy-to-Prompt' feature for Feature Flags, allowing developers to easily copy flag configurations and instructions directly into AI prompts. This functionality streamlines the
arXiv:2604.09076v1 Announce Type: new Abstract: Spatial transcriptomics provides a molecularly rich description of tissue organization, enabling unsupervised discovery of tissue niches -- spatially co
arXiv:2602.10603v3 Announce Type: replace Abstract: Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-voc
arXiv:2512.19396v3 Announce Type: replace Abstract: Contemporary GUI agents, while increasingly capable due to advances in Large Vision-Language Models (VLMs), often operate with a critical limitation
arXiv:2604.08698v1 Announce Type: new Abstract: Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. Unlike natural language, DNA
This Reddit post from r/StableDiffusion discusses a community comparison or showcase involving a 'Zit LoRA' — a Stable Diffusion LoRA model — examining how it performs differently when applied to face
arXiv:2604.09127v1 Announce Type: new Abstract: Lightweight face recognition is increasingly important for deployment on edge and mobile devices, where strict constraints on latency, memory, and energ
arXiv:2604.06832v2 Announce Type: replace Abstract: Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference
arXiv:2604.09125v1 Announce Type: new Abstract: Existing age estimation methods treat each face as an independent sample, learning a global mapping from appearance to age. This ignores a well-document
arXiv:2601.18150v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence
arXiv:2604.06014v2 Announce Type: replace Abstract: We introduce Gated-SwinRMT, a family of hybrid vision transformers that combine the shifted-window attention of the Swin Transformer with the Manhat
GLM-5.1 is Z.AI's next-generation flagship model for agentic engineering, featuring significantly stronger coding capabilities than its predecessor and achieving state-of-the-art performance on SWE-Be
arXiv:2604.09075v1 Announce Type: new Abstract: Large language models increasingly operate under multiple instructions from heterogeneous sources with different authority levels, including system poli