Knowledge catalogue
arXiv:2404.07373v2 Announce Type: replace-cross Abstract: This paper presents a method to synthesize neural network controllers to maximize reward subject to the hard constraint that the feedback syst
arXiv:2606.00673v1 Announce Type: new Abstract: Thermal imaging offers a powerful alternative to visible-spectrum vision under challenging conditions such as low illumination and adverse weather, yet
arXiv:2606.00503v1 Announce Type: cross Abstract: Modifying an attribute in tabular data often introduces an unnatural instance by breaking its relationships with other attributes. The modified instan
arXiv:2606.00662v1 Announce Type: new Abstract: This report presents TAP-JEPA, our runner-up submission to the EPIC-KITCHENS-100 (EK-100) Action Anticipation Challenge at EgoVis 2026. The task is to a
arXiv:2606.01421v1 Announce Type: new Abstract: We show that an array of scatterers which has been designed to have latent ('hidden') symmetries can be used as a sensor. We use the capacitance matrix
arXiv:2606.01106v1 Announce Type: new Abstract: TimeLogicQA evaluates whether video question answering systems can reason over temporal relations such as event existence, ordering, persistence, bounda
arXiv:2606.01112v1 Announce Type: new Abstract: Heterogeneous marine robotic systems composed of an unmanned surface vehicle (USV) and a hybrid remotely operated vehicle (HROV) have shown great potent
Fine-tuning isn't dead, but the way most teams iterate on AI products has split in two. A tiny fraction run continuous RL against their own environments; everyone else has moved the iteration loop out
arXiv:2606.00261v1 Announce Type: new Abstract: Police-reported crash statistics remain the standard input for urban road-safety assessment, but their incompleteness and reporting lag limit their usef
arXiv:2606.00291v1 Announce Type: cross Abstract: In RLHF, each training example contains a prompt x and two candidate responses y,y', and annotators provide pairwise preferences between these respons
Anna Tong / Forbes: Thrive Holdings, a spinoff of Thrive Capital, commits $1B to acquire local accounting firms through its subsidiary, Current, and use AI to automate them — In Thrive Holdings' live-
arXiv:2606.01670v1 Announce Type: cross Abstract: Recently, Generative Recommenders (GRs) have emerged as a transformative recommendation paradigm by replacing traditional item IDs with semantic indic
arXiv:2606.00040v1 Announce Type: cross Abstract: As Generative AI (GenAI) becomes integral to education, fostering GenAI literacy is critical. However, current assessments largely rely on self-report
arXiv:2606.01896v1 Announce Type: cross Abstract: Generated (or synthetic) image data is increasingly used to augment or replace real training datasets when target imagery is scarce, expensive, or bia
arXiv:2606.00321v1 Announce Type: new Abstract: In fulfillment centers, diverse objects move continuously from inbound to outbound operations and can become jammed due to excessive conveyor friction,
arXiv:2602.12724v3 Announce Type: replace Abstract: This study introduces TRANS: Terrain-aware Reinforcement learning for Agile Navigation under Social interactions, a deep reinforcement learning (DRL
arXiv:2606.01457v1 Announce Type: new Abstract: Bayesian optimization is a popular way to optimize expensive systems, where every experiment, simulation, or intervention costs time or money. In its st
arXiv:2606.02350v1 Announce Type: new Abstract: Reconstructing humans and their surrounding environments in a globally consistent 4D space is essential for comprehensive perception. However, prior wor
arXiv:2508.12551v2 Announce Type: replace-cross Abstract: Linux kernel tuning is essential for optimizing operating system (OS) performance, yet remains challenging due to the complex kernel space, sp
arXiv:2511.07438v3 Announce Type: replace Abstract: Cryo-electron microscopy (cryo-EM) is a powerful imaging technique for reconstructing three-dimensional molecular structures from noisy tomographic
arXiv:2606.01708v1 Announce Type: cross Abstract: We study fixed-confidence best-action identification (BAI) in stochastic minimax trees. This problem is increasingly relevant in modern AI planning, w
arXiv:2606.00170v1 Announce Type: cross Abstract: In recent years, emotion recognition based on physiological signals such as electroencephalogram (EEG) has gained considerable attention, as internal
arXiv:2606.02038v1 Announce Type: cross Abstract: Reconstructing spatially continuous daily temperature fields from sparse observations is important for urban climate monitoring and heat-risk analysis
arXiv:2606.00294v1 Announce Type: new Abstract: Temporal language does more than place events on a timeline. In news discourse, references to the past, present, and future can function as rhetorical d
arXiv:2606.02020v1 Announce Type: new Abstract: This paper investigates the entropy dynamics of Chain-of-Thought (CoT) and uncovers a consistent two-phase structure: an Uncertainty Region of explorati
Cloud security startup Upwind Security Inc. today announced it has integrated its runtime security platform with Cisco Cloud Control, the unified platform for agentic information technology operations
arXiv:2606.01443v1 Announce Type: cross Abstract: A central difficulty in training Joint-Embedding Predictive Architectures (JEPAs) is preventing representation collapse. LeJEPA addresses this by enfo
arXiv:2606.00119v1 Announce Type: cross Abstract: Reliable work zone mapping is important for connected and autonomous vehicles (CAVs) to navigate safely and smoothly through work zone areas. Cone-mou
Verification is the hidden bottleneck for knowledge work agents, especially in legal AI — complex, long-horizon work is graded by rubrics with dozens of strict criteria. In new research with @LangChai
arXiv:2606.00704v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, e
arXiv:2509.15394v3 Announce Type: replace Abstract: Accurate electricity demand forecasting is challenging due to the strong multi-periodicity of real-world demand series, which makes effective modeli
arXiv:2606.02096v1 Announce Type: new Abstract: Dynamic scene reconstruction from monocular videos remains highly challenging, as existing methods often struggle to balance global structural coherence
arXiv:2606.02245v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) typically assumes that external knowledge is free, but many high-quality sources are paywalled, licensed, restricte
arXiv:2606.00086v1 Announce Type: new Abstract: Inverse kinematics (IK) is a fundamental problem in robotics, requiring the generation of joint configurations that satisfy target end-effector poses. E
arXiv:2602.12819v2 Announce Type: replace-cross Abstract: In this paper, we present WISE, an open-source audiovisual search engine which integrates a range of multimodal retrieval capabilities into a
@xai @imagine see more about flipbook from @zan2434 and @eddiejiao_obj ! https://x.com/eddiejiao_obj/status/2046975783324004732?s=20 What if your whole computer were just pixels streamed to you from a
you have to give @MicrosoftAI props for training all these in-house from scratch and getting ALL of them to near-SOTA. Mustafa built a full fledged neolab inside Microsoft in 2 years, that now MS full
A lot more to come! We are excited to work closely with NVIDIA on the Cosmos Coalition Introducing the Cosmos Coalition A new global initiative with NVIDIA and leading AI labs to build and open-source
arXiv:2605.30388v1 Announce Type: new Abstract: This paper introduces a new systematic framework for detecting anomalies in maritime Automatic Identification System (AIS) datasets. These anomalies inc
arXiv:2603.28201v2 Announce Type: replace Abstract: We revisit the standard perturbation-based approach of Abernethy et al. (2008) in the context of unconstrained Bandit Linear Optimization (uBLO). We
arXiv:2601.22202v2 Announce Type: replace-cross Abstract: Semantic communication (SemCom) emerges as a transformative paradigm for traffic-intensive visual data transmission, shifting focus from raw d
arXiv:2605.30625v1 Announce Type: cross Abstract: Inferring continuous probability paths from sparse snapshots is a fundamental challenge in domains like single-cell biology, where high-fidelity data
arXiv:2605.31405v1 Announce Type: new Abstract: This paper addresses the challenge of simultaneously compensating for state-dependent uncertainties and enforcing time-varying state constraints in Eule
arXiv:2602.11208v2 Announce Type: replace Abstract: The Earth's subsurface is a cornerstone of modern society, providing essential energy resources like hydrocarbons, geothermal, and minerals while se
arXiv:2605.30582v1 Announce Type: new Abstract: While platforms like Google Scholar and Semantic Scholar track citations for academic papers, no comparable infrastructure exists for monitoring dataset
arXiv:2605.30742v1 Announce Type: new Abstract: This paper addresses the task of temporal sentence grounding (TSG). Although many respectable works have made decent achievements in this important topi
arXiv:2602.17587v2 Announce Type: replace-cross Abstract: We study one-sided and alpha-correct sequential hypothesis testing for data generated by an ergodic, finite-state Markov chain. The null hypot
arXiv:2605.30667v1 Announce Type: cross Abstract: Software tools for reverse engineering executable binary files, such as Ghidra, enable malware analysts to safely conduct robust static analysis witho
llama.cpp b9452 is a release of the LLM inference C/C++ project from the ggml-org repository. This release likely includes updates to the software's core functionality, bug fixes, or new features that
Release b9455 is a build of llama.cpp, a C/C++ implementation for LLM inference . This release represents a specific commit or version update to the llama.cpp project, which is used for running large
Release b9459 is a version of llama.cpp, the C/C++ implementation for LLM inference. The specific release would contain bug fixes, optimizations, or new features for the llama.cpp project, which enabl
Release b9464 is a version of llama.cpp, a project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. This specific release likely contains upd
arXiv:2605.31481v1 Announce Type: new Abstract: As robot control shifts toward large-scale reinforcement learning with in-loop dynamics computation, the community's reliance on CPU-bound libraries suc
arXiv:2605.30976v1 Announce Type: cross Abstract: We study stochastic linear bandits under a natural combination of batching and communication constraints: the time horizon is partitioned into batches
arXiv:2605.30987v1 Announce Type: new Abstract: The tasks of object removal and inpainting 3D Gaussian Splatting (3DGS) scenes face challenges such as 3D consistency across camera views. In comparing
arXiv:2508.18730v2 Announce Type: replace Abstract: Estimating the quality of register transfer level (RTL) designs is crucial in the electronic design automation (EDA) workflow, as it enables instant
arXiv:2605.31110v1 Announce Type: new Abstract: Generalization in robotics requires prior knowledge about how the world is structured, yet this structure changes from one situation to the next. This p
arXiv:2510.14904v3 Announce Type: replace-cross Abstract: Dense Video Object Captioning (DVOC) is the task of jointly detecting, tracking, and captioning object trajectories in a video, requiring the
arXiv:2602.02819v3 Announce Type: replace Abstract: Membership Inference Attacks (MIAs) aim to distinguish training points (members) from unseen data (non-members), and are widely used to quantify mem
arXiv:2602.22968v3 Announce Type: replace Abstract: Understanding how neural networks arrive at their predictions is essential for debugging, auditing, and deployment. Mechanistic interpretability pur