Knowledge catalogue
arXiv:2502.11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particul
arXiv:2608.14614v1 Announce Type: cross Abstract: As AI datacenters retire functional GPUs, vast quantities of still capable accelerators enter secondary markets. This paper investigates whether these
arXiv:2608.16016v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GenAI) can produce high-quality essays, code, and design artefacts, challenging the validity of conventional asses
arXiv:2608.15282v1 Announce Type: cross Abstract: Earth observation foundation models (EOFMs) are emerging as reusable representation frameworks for data-driven retrieval, prediction and process model
arXiv:2608.14645v1 Announce Type: new Abstract: Studying climate change requires reducing uncertainties in CO2 and CH4 emission estimates to better distinguish anthropogenic from natural sources, whic
arXiv:2508.18037v2 Announce Type: replace Abstract: Leveraging information from public data has become increasingly crucial in enhancing the utility of differentially private (DP) methods. Traditional
arXiv:2608.15022v1 Announce Type: new Abstract: Language models hold latent quantities in a form they can report on, and more of a quantity is present in that form when the task requires reusing it fl
arXiv:2608.14594v1 Announce Type: new Abstract: Projected Gradient Descent (PGD) is widely used to evaluate adversarial robustness, typically via final adversarial accuracy, which does not capture mod
arXiv:2608.15517v1 Announce Type: new Abstract: Chain-of-thought reasoning has substantially improved the problem-solving capabilities of multimodal large language models. Fine-grained visual evidence
GLM-5.3 achieves 60 on the Artificial Analysis Intelligence Index, on par with Kimi K3 and up 7 points from GLM-5.2. Once the weights are released it will be tied as the leading open weights model @Za
arXiv:2608.15382v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for healthcare decision support, but their evaluations still reward single-answer accuracy rather
arXiv:2608.15647v1 Announce Type: cross Abstract: Semantic segmentation of very-high-resolution (VHR) remote sensing imagery increasingly benefits from strong pretrained hierarchical encoders, yet exp
arXiv:2608.15016v1 Announce Type: cross Abstract: Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate reco
arXiv:2608.16628v1 Announce Type: new Abstract: Modern Multimodal Retrieval-Augmented Generation (M-RAG) systems are fundamentally limited by the binary connectivity paradigm of traditional simple gra
arXiv:2603.00600v2 Announce Type: replace Abstract: Active perception - the ability of a robot to proactively select viewpoints to acquire task-relevant information - is essential for robust operation
arXiv:2608.15731v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) deployed in high-risk domains, such as healthcare and autonomous driving, must be not only accurate but also understandabl
arXiv:2608.14692v1 Announce Type: cross Abstract: Personalized, generative AI systems increasingly adapt their behavior to individual users over time, fundamentally changing model behavior. While exis
If you’re building an “agent over your PDFs” in 2026, one of the most underrated things you can do is to provide exact grounding back to the source document for any agentic answers. Specifically, show
arXiv:2608.15689v1 Announce Type: cross Abstract: This study presents a hybrid epidemiological and behavioural framework to simulate the spread of health misinformation on social media. We extend the
arXiv:2608.14896v1 Announce Type: new Abstract: Large language models work well on English and behave in poorly understood ways on languages typologically far from it. Japanese is a clean example, whe
arXiv:2608.15579v1 Announce Type: cross Abstract: Industrial software-engineering teams increasingly need LLM agents that turn bug reports into correct patches, yet benchmark-scale operation adds long
arXiv:2608.15535v1 Announce Type: new Abstract: We present L3Cube-IndicQuest v2, a large-scale gold-standard multilingual question-answering benchmark for evaluating the India-specific factual knowled
arXiv:2608.16763v1 Announce Type: new Abstract: Financial document validation in production, such as payroll auditing, tax compliance, and loan underwriting, demands exceptional accuracy, consistency,
arXiv:2608.16539v1 Announce Type: cross Abstract: Large Audio Language Models (LALMs) have made rapid progress on standardized benchmarks, yet their deployment in practical media workflows, curation,
arXiv:2506.07449v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLMs) have driven their adoption in recommender systems through Retrieval-Augmented Generation (RAG)
arXiv:2601.23049v2 Announce Type: replace Abstract: Medical calculators are fundamental to quantitative, evidence-based clinical practice. However, their real-world use is an adaptive, multi-stage pro
arXiv:2608.14783v1 Announce Type: new Abstract: Part-aware 3D object generation is essential for graphics applications such as controllable modeling, editing, and articulation, where objects are repre
arXiv:2608.16357v1 Announce Type: cross Abstract: Autonomous agents share a transport and can call each other's tools, but they cannot share what they know: no protocol lets two agents' memories recon
arXiv:2406.00971v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have recently seen significant advancements through integrating with Large Language Models (LLMs). The VLMs, whi
arXiv:2608.15549v1 Announce Type: cross Abstract: Programming small social robots from natural-language instructions requires more than invoking isolated APIs. Interactive tasks combine reactive physi
arXiv:2608.15437v1 Announce Type: cross Abstract: Multimodal bird's-eye-view (BEV) perception combines LiDAR depth accuracy with dense camera semantics, but its high computational cost and imperfect s
arXiv:2608.15045v1 Announce Type: new Abstract: We present MOSS-VL, an open vision-language model family that treats real-time interaction -- perceiving while it speaks -- as a first-class capability.
arXiv:2608.16181v1 Announce Type: cross Abstract: Recent advances in large language models have enabled a new class of agentic data science systems that allow users to complete complex data science wo
Muse Glimmer 30B is now available on Fireworks' Dedicated Training API for both LoRA and Full-Parameter fine-tuning. This is a U.S.-developed, open-weight model and one of the strongest of its size fo
arXiv:2608.15919v1 Announce Type: cross Abstract: Retrieval-Augmented Generation over knowledge graphs (Graph-RAG) has emerged as a powerful paradigm for grounding large language models in domain-spec
arXiv:2608.15573v1 Announce Type: new Abstract: Reliable long-horizon planning remains a key challenge in end-to-end autonomous driving. By accounting for future motion evolution and potential consequ
arXiv:2608.16225v1 Announce Type: new Abstract: Standard Transformers have proven effective in point cloud object classification, but their performance in dense prediction tasks within complex scenes
arXiv:2608.14881v1 Announce Type: new Abstract: AI co-scientists that generate hypotheses, retrieve related work, design experiments, execute code, and draft full papers are beginning to change how re
arXiv:2608.16419v1 Announce Type: cross Abstract: Large language models can describe mechanisms, yet scalable post-training still depends on costly, manually curated biological reasoning traces. Here
arXiv:2608.15314v1 Announce Type: new Abstract: Ultra-reliable low-latency communication (URLLC) requires precise identification of spatial regions where the signal-to-noise ratio (SNR) falls below an
arXiv:2311.02629v5 Announce Type: replace Abstract: We introduce the Pointer Q-Network (PQN), a hybrid neural architecture that integrates model-free Q-value policy approximation with Pointer Networks
arXiv:2608.16276v1 Announce Type: cross Abstract: Debate is a structured form of persuasive communication that trains argument construction, rebuttal, oral delivery, and audience awareness. These skil
arXiv:2608.15583v1 Announce Type: new Abstract: While Text-to-Image (T2I) diffusion models have achieved remarkable success, precise spatial and orientational control in multi-object scenes remains a
arXiv:2603.08590v3 Announce Type: replace Abstract: Text-to-motion generation has advanced with larger corpora and stronger generators, yet many models still rely on holistic frame- or clip-level late
arXiv:2602.08261v2 Announce Type: replace Abstract: Auto-bidding systems strive to maximize marketing value while maintaining high compliance with efficiency constraints, such as Target Cost-Per-Actio
arXiv:2608.16168v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction hist
arXiv:2608.15269v1 Announce Type: new Abstract: Long-horizon robot policies require compact access to recent observations and reusable experience without expanding the vision-language-action (VLA) con
arXiv:2608.14947v1 Announce Type: new Abstract: Detecting opioid craving from wearable physiological signals is critical yet difficult, with the potential to support proactive interventions for indivi
arXiv:2608.15251v1 Announce Type: new Abstract: Integrated 3D reconstruction from aerial-ground images is essential for generating high-precision urban 3D models, yet severe variations in viewpoint, s
arXiv:2608.15787v1 Announce Type: cross Abstract: Two Mixture-of-Experts (MoE) forward passes can share every weight yet route the same token through different experts. This creates a possible blind s
arXiv:2608.15018v1 Announce Type: new Abstract: Deploying large language models (LLMs) for inference on edge devices is challenging due to severe memory and bandwidth constraints. While speculative de
arXiv:2608.16081v1 Announce Type: new Abstract: Open-weight and frontier vision-language models (VLMs) perform well on general image understanding, but their ability to interpret fine-grained hand ges
arXiv:2608.15336v1 Announce Type: new Abstract: Current surgical scene graph generation methods depend on dense multi-modal supervision and specialized hardware (synchronized RGB-D sensors, calibratio
arXiv:2608.16187v1 Announce Type: cross Abstract: AI-assisted development tools generate vulnerable code at significant rates, yet few automated mechanisms exist to detect, enrich, fix, and verify sec
arXiv:2510.03885v4 Announce Type: replace Abstract: In this paper, we demonstrate that mobile manipulation policies utilizing a 3D latent map achieve stronger spatial and temporal reasoning than polic
arXiv:2608.16384v1 Announce Type: new Abstract: Universal visual representations require adaptation mechanisms that adapt across heterogeneous domains without fragmenting knowledge into domain-specifi
arXiv:2608.16741v1 Announce Type: new Abstract: Long-term manipulation planning requires robots to reason not only about immediate task success but also about how current decisions affect future inter
arXiv:2608.15165v1 Announce Type: new Abstract: Large language model (LLM) agents can continually improve without parameter updates by converting historical experience into reusable procedural knowled
arXiv:2608.16172v1 Announce Type: new Abstract: At every re-observation point in a hierarchical Vision-Language-Action (VLA) system, two interface decisions must be made: when to terminate the current
arXiv:2608.15452v1 Announce Type: new Abstract: Current flow matching models learn to transport the source i.i.d. Gaussian noise into the target distribution of natural images, yet this source distrib