Knowledge catalogue
arXiv:2607.19857v1 Announce Type: cross Abstract: Language-guided aerial perception aims to understand user-specified tiny targets in complex unmanned aerial vehicle (UAV) scenes. In real UAV deployme
arXiv:2607.19530v1 Announce Type: new Abstract: Many Blind and Low-Vision (BLV) people rely on guide dogs for moment-to-moment navigation, such as staying on path and avoiding obstacles and pedestrian
The math behind reinforcement learning (RL) post-training for large language models (LLMs) is notoriously unforgiving. As frontier AI labs push the boundaries of reasoning and coding models using RL p
arXiv:2607.19826v1 Announce Type: new Abstract: Action Quality Assessment (AQA) aims to objectively evaluate performance quality from action videos. Most existing methods follow a ``one-by-one'' parad
arXiv:2512.05462v2 Announce Type: replace-cross Abstract: Pharmaceutical drug discovery demands machine learning (ML) infrastructure that goes beyond general-purpose Machine Learning Operations (MLOps
arXiv:2607.20284v1 Announce Type: new Abstract: The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU
arXiv:2607.19951v1 Announce Type: new Abstract: Cross-view geo-localization between UAV and satellite imagery remains a fundamental yet highly challenging task, especially under large off-nadir views
arXiv:2607.19944v1 Announce Type: cross Abstract: A two-stage mixed-integer linear programming framework is introduced for subsea pipeline incident response planning, jointly optimizing Subsea Docking
arXiv:2510.18348v2 Announce Type: replace-cross Abstract: State-of-the-art perceptive Reinforcement Learning controllers for legged robots typically either (i) impose oscillator-or IK-based gait prior
arXiv:2603.15403v2 Announce Type: replace Abstract: This paper presents a comprehensive pipeline for recognizing objects targeted by human pointing gestures using RGB images. As human-robot interactio
arXiv:2607.19400v1 Announce Type: new Abstract: Pre-trained foundation models (FMs) have begun transforming single-cell genomics, but scaling them raises privacy concerns. Moreover, unlike text data,
arXiv:2607.17820v2 Announce Type: replace Abstract: Training-free few-shot adaptation methods have gained significant attention recently in the context of Vision-language Models (VLMs). Yet, current b
arXiv:2607.18773v1 Announce Type: new Abstract: Accurate skin lesion classification can benefit from lesion segmentation masks, but requiring masks or an auxiliary segmentation model during inference
arXiv:2607.16195v2 Announce Type: replace Abstract: We identify a structured confound in Reinforcement Learning from Human Feedback (RLHF). Pairwise preference labels are intended to reflect the compa
arXiv:2607.19403v1 Announce Type: cross Abstract: Validating federated learning frameworks on real clinical data is an essential step between proof-of-concept demonstrations in controlled synthetic en
arXiv:2607.20061v1 Announce Type: new Abstract: Embodied visual tracking (EVT) requires a mobile agent to continuously follow a specific target described in natural language using only onboard vision.
arXiv:2607.20090v1 Announce Type: cross Abstract: Retrieval-augmented large language models frequently face contexts that interleave useful evidence with misleading statements or instruction-like cont
arXiv:2607.20116v1 Announce Type: new Abstract: Global visual localization of unmanned aerial vehicles (UAVs) using remote-sensing reference maps has attracted increasing attention. However, acquisiti
arXiv:2509.14925v2 Announce Type: replace Abstract: Deep reinforcement learning (DRL) methods, though powerful, often lack transparency, which limits their adoption in critical domains. We apply Self-
arXiv:2607.20162v1 Announce Type: new Abstract: The growing demand for intelligent processing at the edge of IoT networks is constrained by the severe computational and memory limitations of microcont
arXiv:2607.20216v1 Announce Type: cross Abstract: Malware analysis demands rapid interpretation of complex detonation reports spanning filesystem, network, and process behaviours. While large language
arXiv:2607.20255v1 Announce Type: cross Abstract: LLM-driven autonomous agents are reshaping offensive security. Unlike traditional penetration-testing tooling -- deterministic, narrowly scoped, and o
arXiv:2607.19383v1 Announce Type: cross Abstract: Pretrained generative foundation models cast forecasting as conditional generation from a learned predictive distribution and forecast unseen series z
arXiv:2607.19532v1 Announce Type: cross Abstract: Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models,
arXiv:2607.19621v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult du
arXiv:2607.19971v1 Announce Type: new Abstract: Accurate motion prediction of surrounding agents and safe motion planning are two closely coupled key tasks for social robot navigation in crowded envir
arXiv:2607.20027v1 Announce Type: new Abstract: Short-term Heart Rate Variability (HRV) forecasting could provide clinicians with actionable lead time for detecting autonomic dysfunction and adverse c
Scientists today face challenges of extraordinary scale and complexity. From shaping and simulating the intricate dynamics of fusion plasma, to exploring the vast search space of new materials, to mak
AMD says it's going to invest up to $5 billion in Anthropic, while helping to expand the AI company's computing power, according to an announcement on Wednesday. As part of the new partnership, Anthro
One thing I noticed in American politics, whenever the government wants to push unpopular actions or laws, they often introduce fear to convince the public to support them. This is actually how i view
Most AI SDKs are a wrapper around one engine on one platform. We built the opposite. 7 SDKs. Swift, Kotlin, Flutter, React Native, Web, Electron, rcli. Python. All of them are thin skins over one C++
As AI models are now finding vulnerabilities faster than we can fix them, our approach to securing software must be built on highly efficient and capable models. Which brings us to our third (!) model
In Google Cloud, Identity and Access Management (IAM) helps you maintain access control over your cloud resources and operations. While it includes other features, this is its primary purpose. If you
Great article. I love the 'CERN for AI' idea from Gary Marcus, and also the recent frontier standards body article from Demis Hassabis feels less like competing proposals than two halves of the same i
Mistral is announcing an expanded global strategic partnership with @Microsoft to give enterprises and regulated industries frontier AI they can control. As Mistral is expanding its AI compute capacit
Run Devin Outposts on @nvidia Brev to give Devin access to GPU infrastructure for debugging training runs, inspecting GPU state, reproducing failures, and validating fixes on the hardware where the wo
Together AI’s recent fireside chat with Y Combinator’s Andy Gupta explains why speed to launch and scalability were the key factors in selecting a partner for YC’s first dedicated GPU cluster. The con
Erin Davis calls it the “SuperDuperPOD.” That’s two things in one name: pharmaceutical giant Bristol Myers Squibb (BMS) already runs one of the largest AI clusters in life sciences, with serious resul
arXiv:2607.13237v1 Announce Type: new Abstract: Precise spatial-temporal annotation of laparoscopic videos is time-consuming and requires expert knowledge. We propose a human-in-the-loop knowledge acq
arXiv:2607.13205v1 Announce Type: cross Abstract: Attention-based KV cache eviction (H2O and its descendants) compresses the memory-constrained state of a long-context model by ranking tokens on accum
arXiv:2607.13579v1 Announce Type: cross Abstract: Enabling quadrupedal robots to traverse complex terrains-from rugged outdoor environments to urban landscapes-requires seamless integration of multipl
arXiv:2607.13123v1 Announce Type: cross Abstract: Cybersecurity is the practice of protecting systems, networks, and data from digital attacks. Cyberpsychology (CPSY) is defined as the use of psycholo
arXiv:2607.13524v1 Announce Type: new Abstract: Active 3D reconstruction requires selecting informative viewpoints under limited sensing budgets. In multi-agent settings, coordination inefficiencies s
arXiv:2510.15371v2 Announce Type: replace-cross Abstract: Classification of electroencephalogram (EEG) signals obtained during motor imagery (MI) has substantial application potential, including commu
arXiv:2607.13938v1 Announce Type: new Abstract: Inverse Reinforcement Learning (IRL) algorithms are powerful tools for learning from and generalizing expert demonstrations, but they often rely on unco
arXiv:2607.13685v1 Announce Type: new Abstract: The rapid evolution of image generation has produced numerous within-family variants, making source-model attribution of suspect images increasingly imp
arXiv:2607.14004v1 Announce Type: new Abstract: Most reported gains from agent-optimization methods are one-shot: an agent is optimized against a fixed benchmark and the resulting improvement is repor
arXiv:2607.13789v1 Announce Type: new Abstract: This paper introduces the Dynamical Vehicle Orienteering Problem (DVOP), a generalization of the Orienteering Problem (OP). The OP maximizes the reward
arXiv:2607.13093v1 Announce Type: cross Abstract: On-device LLM inference faces a trilemma of response latency, limited hardware resources and user privacy. Full cloud inference delivers strong comput
arXiv:2607.13330v1 Announce Type: cross Abstract: Diffusion-based text-to-audio generative models such as AudioLDM achieve high perceptual quality and strong semantic consistency; however, their pract
arXiv:2607.13792v1 Announce Type: new Abstract: Most daily activities are inherently procedural. However, existing evaluations for egocentric video understanding seldom address procedural understandin
arXiv:2607.13469v1 Announce Type: cross Abstract: The banking sector increasingly relies on automated systems to monitor electronic transactions for signs of fraud, yet conventional rule-based approac
arXiv:2607.13960v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as den
arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly
arXiv:2607.13080v1 Announce Type: cross Abstract: Autonomous coding agents force engineering organizations to choose between API-based frontier models -- strong reasoning at high token cost -- and on-
arXiv:2607.13497v1 Announce Type: new Abstract: In expeditionary medical facilities, routine patient transport imposes a compounding burden of personal protective equipment consumption, staff diversio
arXiv:2607.14072v1 Announce Type: new Abstract: Bioacoustic foundation models rely on large-scale citizen science platforms like Xeno-Canto for geographically and ecologically diverse data. Recent wor
arXiv:2603.16103v2 Announce Type: replace Abstract: 3D Gaussian Splat (3DGS) enables high-fidelity, real-time novel view synthesis by representing scenes with large sets of anisotropic primitives, but
arXiv:2601.02023v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly utilize massive context windows as working memory for autonomous tasks, their reliability fluctua
arXiv:2607.13328v1 Announce Type: cross Abstract: Personalized recommendation systems are central to modern e-commerce and retail platforms, but they typically rely on centralized storage of detailed