Knowledge catalogue
arXiv:2607.03177v1 Announce Type: cross Abstract: Traditional reinforcement learning (RL) for recovery in autonomous systems lacks causal understanding and generalizes poorly to novel failure scenario
arXiv:2607.04987v1 Announce Type: new Abstract: Cell-type deconvolution, the task of estimating the proportions of constituent cell types in a heterogeneous biological sample, is a core problem in com
arXiv:2607.03277v1 Announce Type: new Abstract: Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large,
arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text des
arXiv:2607.02845v1 Announce Type: cross Abstract: Multi-view robotic manipulation methods with the attention mechanism have recently achieved significant progress in both training efficiency and task
arXiv:2607.04599v1 Announce Type: new Abstract: Accurate 3D medical segmentation is limited by anatomical variability and high computational costs. While knowledge distillation (KD) offers a route for
DOGE shut down USAID, established by JFK in 1961. Before being shut down, the US Agency for International Development (USAID) was the largest funding agency for humanitarian and development aid worldw
arXiv:2607.02561v1 Announce Type: cross Abstract: Consumer depth sensors such as the LiDAR scanner on recent iPhones provide metric range, but their useful range is short and their returns are sparse.
arXiv:2607.04740v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) measures gene expression while preserving spatial context, but its high cost and low throughput leave public datasets small
arXiv:2508.12116v2 Announce Type: replace-cross Abstract: As numerous instruction-tuning datasets continue to emerge, dynamically balancing and optimizing their mixtures has become a critical challeng
arXiv:2508.16170v2 Announce Type: replace-cross Abstract: MultiModal Recommendation (MMR) systems have emerged as a promising solution for improving recommendation quality by leveraging rich item-side
arXiv:2607.04668v1 Announce Type: cross Abstract: On-device LLM decoding is a hard-barriered CPU-SIMD computation that wants every core for milliseconds per token, while the rest of the OS wants those
Elon has the perfect opportunity to lead the US open source AI by dropping some weights on Hugging Face tomorrow. not optimistic he does, but fingers crossed. perfect moment for @SpaceXAI. The solutio
arXiv:2607.03752v1 Announce Type: cross Abstract: Measuring the extent to which emergent languages encode the visual content of their inputs is an open problem. We refer to this property as visual ref
arXiv:2501.14750v3 Announce Type: replace-cross Abstract: Carbon emissions significantly contribute to climate change, and carbon credits have emerged as a key tool for mitigating environmental damage
arXiv:2607.04490v1 Announce Type: new Abstract: Facial expression recognition (FER) is crucial for social interaction in mixed reality environments that employ head-mounted displays (HMD). However, co
arXiv:2607.04416v1 Announce Type: new Abstract: Sri Lanka has experienced a decade of progressive forest degradation and rising atmospheric pollution, yet district-level respiratory admissions have pa
arXiv:2607.04548v1 Announce Type: cross Abstract: Novel category discovery aims to identify unseen classes from unlabeled data by transferring knowledge from labeled categories, but most existing meth
arXiv:2607.03703v1 Announce Type: new Abstract: Reinforcement Learning (RL) has emerged as a powerful paradigm for adaptive traffic signal control. However, in safety-critical infrastructure like traf
arXiv:2607.05095v1 Announce Type: new Abstract: Temporal Graph Neural Networks (TGNNs) are widely used for learning from dynamic graphs in applications such as recommendation, social network analysis,
arXiv:2510.15686v2 Announce Type: replace Abstract: Learning coordinated behaviors for multi-robot systems from only a few demonstrations is difficult because temporal task dependencies and spatial tr
arXiv:2512.21196v2 Announce Type: replace Abstract: Collective motion inspired by animal groups offers powerful design principles for autonomous aerial swarms. We present a bio-inspired 3D flocking al
arXiv:2607.04750v1 Announce Type: new Abstract: We present FM-ChangeNet, a pathwise-supervised framework for change detection that reformulates bi-temporal reasoning as continuous transport in feature
arXiv:2607.03798v1 Announce Type: cross Abstract: Symmetry is everywhere in nature and society. Geometric deep learning exploits symmetries in data to improve the performance and efficiency of deep le
arXiv:2603.19834v3 Announce Type: replace Abstract: Novel view synthesis has recently been revolutionized by 3D Gaussian Splatting (3DGS), which enables real-time rendering through explicit primitive
arXiv:2602.16512v2 Announce Type: replace Abstract: Prompting schemes such as Chain of Thought, Tree of Thoughts, and Graph of Thoughts can significantly enhance the reasoning capabilities of large la
arXiv:2512.09423v2 Announce Type: replace Abstract: Learning natural body motion remains challenging due to the strong coupling between spatial geometry and temporal dynamics. Embedding motion in phas
arXiv:2312.15320v3 Announce Type: replace-cross Abstract: Individuals with suspected rare genetic disorders often undergo multiple clinical evaluations, imaging studies, laboratory tests, and genetic
arXiv:2508.03750v2 Announce Type: replace-cross Abstract: Early and accurate glaucoma detection is critical to prevent irreversible vision loss, yet existing AI methods often rely on unimodal inputs a
GLM 5.2, running on Together AI's platform, has achieved the top ranking on Artificial Analysis benchmarks for both output speed and latency metrics. This announcement highlights Together AI's infrast
arXiv:2407.09632v3 Announce Type: replace-cross Abstract: We introduce a rigorous mathematical framework for Granger causality in extremes, designed to identify causal links from extreme events in tim
arXiv:2607.04353v1 Announce Type: cross Abstract: Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell image
Hermes Agent can now export your agent sessions, or sets of sessions, into a variety of formats and places. Get full conversations out in HTML, Markdown, JSON and more, or upload entire datasets of yo
arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt
arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit
arXiv:2603.24025v2 Announce Type: replace Abstract: Unsupervised learning of high-dimensional data is challenging due to irrelevant or noisy features obscuring underlying structures. It's common that
arXiv:2607.04735v1 Announce Type: cross Abstract: When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two global
arXiv:2607.05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly
arXiv:2607.03125v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) offers powerful control for industrial cyber-physical systems (ICPSs), but its 'black-box' exploration risks violating
arXiv:2605.11012v2 Announce Type: cross Abstract: Programming the static friction of mechanical interfaces is critical for soft robotics, haptics, and precision gripping. Static friction is governed b
arXiv:2512.08854v3 Announce Type: replace Abstract: It has been hypothesized that achieving the data efficiency of human visual perception requires a generative approach in which internal representati
arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi
arXiv:2607.03320v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) generates natural-language descriptions of semantic changes between paired remote sensing images (RSIs),
arXiv:2607.05263v1 Announce Type: new Abstract: This paper concerns the problem of unsupervised temporal action segmentation for long, untrimmed videos. Recent successful approaches follow a joint rep
arXiv:2607.04638v1 Announce Type: new Abstract: Referring expression comprehension (REC) aims to localize the object in an image described by natural language. In Weakly supervised REC (WREC), existin
arXiv:2602.09530v2 Announce Type: replace-cross Abstract: We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and n
arXiv:2604.01641v2 Announce Type: replace Abstract: We introduce LivingWorld, an interactive framework for generating 4D worlds with environmental dynamics from a single image. While recent advances i
arXiv:2607.04412v1 Announce Type: new Abstract: Reinforcement learning (RL) for non-verifiable instruction following increasingly relies on LLM judges with prompt-specific rubrics as reward signals. W
arXiv:2607.03699v1 Announce Type: new Abstract: In many multisensor systems, measurements from different sensors are subject to unknown relative time delays. Accurate state estimation requires that de
arXiv:2607.04531v1 Announce Type: cross Abstract: Low-precision neural networks are attractive for resource-constrained hardware, but fixed-point arithmetic introduces failure modes that are often hid
arXiv:2607.03875v1 Announce Type: new Abstract: Close-up rendering, zooming into a scene well beyond any training camera, is important for virtual production and interactive 3D content, yet remains an
arXiv:2509.23960v2 Announce Type: replace-cross Abstract: Co-optimizing safety and performance in large-scale multi-agent systems remains a fundamental challenge. Existing approaches based on multi-ag
arXiv:2607.03973v1 Announce Type: new Abstract: Concept erasure aims to remove a target concept from a representation while preserving the other information encoded in it. This is difficult because re
arXiv:2607.04139v1 Announce Type: new Abstract: Self-supervised learning (SSL) shows strong potential for cross-dataset transfer by improving feature representation and generalization. However, its ap
arXiv:2607.04133v1 Announce Type: new Abstract: Causal discovery with nonlinear mechanisms and latent confounders remains challenging. Existing methods often rely on either linear assumptions or causa
arXiv:2607.05167v1 Announce Type: new Abstract: Many real-world systems are organized as networks where spatio-temporal dynamics unfold along connections and not discretely between nodes. Examples inc
arXiv:2607.04391v1 Announce Type: new Abstract: Long-term memory remains a structural weakness of AI agents. The dominant approach, retrieval-augmented generation (RAG), relies on embedding-based simi
Karissa Bell / Engadget: Meta says Muse Image includes an invisible watermarking system called Content Seal and previews a web tool to check whether an image was generated with Meta AI — It has rate l
arXiv:2510.22298v2 Announce Type: replace-cross Abstract: Uncovering the causal mechanisms of complex real-world systems remains a significant challenge, as these systems often entail high data collec
arXiv:2211.10872v2 Announce Type: replace Abstract: Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability t