Knowledge catalogue
arXiv:2609.39148v1 Announce Type: new Abstract: AI agents can externalize what they learn from past tasks into reusable skills, such as procedures, checklists, code, or other executable artifacts, tha
arXiv:2609.38374v1 Announce Type: new Abstract: Representing scientific papers as points in a space lets us search for similar papers and inquire about how fields relate to one another and drive innov
arXiv:2609.38588v1 Announce Type: new Abstract: Although multicopter drones are traditionally designed for 'perception-only' tasks, like mapping and exploration, recent work has sought to develop Unma
arXiv:2609.39190v1 Announce Type: new Abstract: A deep classifier is defined not only by the decision it produces, but also by the sequence of transformations through which that decision is formed. Tr
arXiv:2609.38622v1 Announce Type: new Abstract: Reconstructing and animating water scenery from nature produces compelling and immersive visual experiences. Previous work examined this task from the p
arXiv:2609.39013v1 Announce Type: new Abstract: EVICALC, our system for the DocSem shared task, achieved 8.61% joint accuracy on 1,730 tasks in the official final test evaluation. It reads a PDF, sele
arXiv:2609.39102v1 Announce Type: cross Abstract: Self-evolving search agents build their own training curricula by jointly optimizing a proposer that generates questions and a solver that answers the
arXiv:2609.39837v1 Announce Type: new Abstract: Policy mirror descent (PMD) enjoys fast convergence in regularized Markov decision processes (MDPs), but existing guarantees often rely on exact or incr
Hi everyone — I'm behind Autonomous Workday, and I'm sharing an English-language architecture walkthrough about building an event-driven workflow around local inference. The proposed flow separates fi
arXiv:2609.38918v1 Announce Type: new Abstract: Flow Matching (FM) learns a velocity field whose ODE transports a simple source distribution to a target law. Existing finite-sample theory largely trea
arXiv:2609.39305v1 Announce Type: new Abstract: Safe navigation in dynamic environments requires anticipating future environmental states to account for spatiotemporal risks, specifically when and whe
arXiv:2609.35618v2 Announce Type: replace Abstract: The question of AI consciousness is one of the most urgent pre-emptive problems in philosophy and computer science, yet progress is hampered by a ca
arXiv:2609.38690v1 Announce Type: new Abstract: Spatial transcriptomics enables spatially resolved gene expression analysis from slide-level images while preserving morphological features, providing v
arXiv:2609.38519v1 Announce Type: new Abstract: Egocentric gaze prediction enables many downstream applications but remains challenging, as human gaze is inherently stochastic. This stochasticity is c
arXiv:2511.11689v4 Announce Type: replace-cross Abstract: Generative AI chatbots built for mental health could extend access to care, but evidence from real-world use is limited. We report a single-ar
arXiv:2609.40317v1 Announce Type: new Abstract: While talking head generation has advanced rapidly, generating natural listener behavior in dyadic conversations, which know when to react, how to react
arXiv:2609.40047v1 Announce Type: new Abstract: Gromov-Wasserstein multidimensional scaling (GW-MDS) learns low-dimensional representations from relational data but remains transductive, providing no
arXiv:2609.39883v1 Announce Type: new Abstract: Video temporal grounding supports applications such as video search, content review, and automated editing by localizing events described in natural lan
arXiv:2609.39336v1 Announce Type: new Abstract: Understanding the fundamental mechanisms of learning is essential for designing systems with strong generalization. Recent studies have shown that incre
arXiv:2607.15870v2 Announce Type: replace Abstract: Human label variation in natural language inference is increasingly treated as signal rather than noise, but how much of it formal semantic structur
arXiv:2609.39127v1 Announce Type: new Abstract: Satellite-ground localization estimates the planar position and yaw orientation of a ground camera within a geo-referenced satellite image. Most recent
arXiv:2507.12133v2 Announce Type: replace Abstract: Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Finge
arXiv:2609.40347v1 Announce Type: new Abstract: We introduce VideoMSN, a Masked Siamese Network framework for efficient self-supervised spatio-temporal representation learning in videos. Instead of re
arXiv:2609.39194v1 Announce Type: new Abstract: Wireless split learning (SL) reduces on-device computation by offloading upper layers to a server, yet transmitting high-dimensional intermediate featur
arXiv:2504.06209v2 Announce Type: replace Abstract: Predicting future observations plays a central role in machine learning, biology, economics, and many other fields. It lies at the heart of organiza
arXiv:2609.39120v1 Announce Type: new Abstract: On-policy distillation (OPD) improves reasoning by providing token-level supervision from a teacher on a student's own trajectories. Existing methods pr
arXiv:2603.02767v4 Announce Type: replace-cross Abstract: Image--text contrastive pretraining has become a dominant paradigm for visual representation learning, yet existing methods often yield repres
jes, a jev open-source guardrails project LangChain Ambassador @EdenEmarco177 has been working on It uses LangChain’s TypeSafeClassifier under the hood. The docs include a LangChain middleware example
arXiv:2609.39938v1 Announce Type: cross Abstract: Hour-scale audio-visual question answering is constrained by a context dilemma: dense whole-recording encoding rapidly exhausts context limits, wherea
arXiv:2609.38789v1 Announce Type: new Abstract: Reconstruction errors in multivariate time-series anomaly detection may not reliably distinguish abnormal behavior from benign deviations. Language-deri
arXiv:2603.06281v3 Announce Type: replace Abstract: Generative zero-shot learning (ZSL) synthesizes visual features for unseen classes by learning a semantic-conditioned generator from seen classes. S
arXiv:2609.38608v1 Announce Type: new Abstract: When can we learn from biased samples? We study regression when outcomes are observed only after passing through selection filters that depend on both c
arXiv:2609.40055v1 Announce Type: cross Abstract: On-policy distillation (OPD) provides dense supervision directly on student-generated trajectories, making it an effective post-training strategy for
arXiv:2609.39583v1 Announce Type: cross Abstract: We present the results of extbf{MADGRAV}, a deep-learning-based search for high-mass compact binary coalescences, applied to the data collected by the
arXiv:2609.38746v1 Announce Type: new Abstract: How can a 3D reconstruction system acquire and retain useful information to understand the geometry of a scene from partial views under a limited comput
arXiv:2609.40041v1 Announce Type: new Abstract: We present MGhana-ST, a speech translation dataset for four low-resource Ghanaian language varieties: Ga, Twi (Akuapem and Asante), Ewe, and Fante. MGha
arXiv:2609.39212v1 Announce Type: cross Abstract: We study additive regression under a potentially non-product random design on [0,1]^d, allowing the dimension d to grow with the sample size n. We int
arXiv:2609.39525v1 Announce Type: cross Abstract: Casting Bayesian inference as a neural network optimization problem targeting an amortized posterior is attractive, as it extends to otherwise intract
arXiv:2609.38854v1 Announce Type: cross Abstract: Length scaling during reinforcement-learning (RL) post-training is often viewed as a sign of improved reasoning ability, especially on difficult probl
arXiv:2406.13547v2 Announce Type: replace Abstract: ModSecurity is widely recognized as the standard open-source Web Application Firewall (WAF), maintained by the OWASP Foundation. It detects maliciou
arXiv:2609.39915v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires embodied agents to generate actions based on instructions and observations. General-purpose multimodal agents
arXiv:2609.39017v1 Announce Type: new Abstract: Reliable dexterous manipulation requires continuous estimation of object geometry and hand-object contact throughout interaction. With egocentric sensin
arXiv:2609.38360v1 Announce Type: cross Abstract: On-policy distillation (OPD) has recently emerged as a promising post-training paradigm in which the student learns from trajectories generated by its
arXiv:2609.40035v1 Announce Type: new Abstract: The policy-gradient theorem gives the exact gradient under the current policy, but finite on-policy samples may miss rare high-return trajectories. We s
arXiv:2609.39975v1 Announce Type: cross Abstract: This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluati
arXiv:2609.40102v1 Announce Type: new Abstract: Cable-suspended aerial manipulation offers a lightweight architecture for cooperative transportation and physical interaction, yet the passive mechanica
arXiv:2609.38782v1 Announce Type: new Abstract: Conversational agents increasingly interact with children, yet evidence on how their design shapes children's susceptibility to persuasion comes almost
arXiv:2609.38427v1 Announce Type: cross Abstract: Major venues now publish detailed rules about how authors, reviewers, and area chairs may use AI, and those rules differ by role, by task, and by what
arXiv:2609.38788v1 Announce Type: new Abstract: Organizations started listening to employees through conversational AI agents alongside structured surveys. Little is known about what these channels ch
arXiv:2609.38890v1 Announce Type: new Abstract: Outcome-based reinforcement learning (RL) post-trains vision--language--action policies using terminal success signals, but assigns the same trajectory-
arXiv:2609.39789v1 Announce Type: cross Abstract: Real-world time series forecasting systems operate under non-stationary data streams, where forecasting performance may degrade over time. Although re
arXiv:2609.38780v1 Announce Type: cross Abstract: Audio is increasingly used for human activity recognition (HAR) because it captures object interactions, environmental events, and contextual cues in
arXiv:2609.39960v1 Announce Type: new Abstract: 4D scene reconstruction aims to recover the evolving geometry, appearance, and motion of dynamic environments from visual observations. Despite substant
arXiv:2602.23321v2 Announce Type: replace-cross Abstract: Using advanced machine learning techniques, we developed a method to reconstruct the arrival direction and energy of ultra-high-energy cosmic
arXiv:2609.38598v1 Announce Type: new Abstract: Partially observable environments pose a fundamental challenge in deep reinforcement learning, requiring agents to compress temporal information from ob
arXiv:2609.39306v1 Announce Type: cross Abstract: Iterative self-distillation enables LLM agents to learn from successive deployments, offering a path toward recursive self-improvement (RSI). Yet our
arXiv:2609.39275v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own generated prefixes with token-level teacher feedback, but transmitting or storing the teacher's
arXiv:2609.40158v1 Announce Type: new Abstract: We focus on legible robot motion generation in social navigation settings. Legibility in human-robot interaction (HRI) is often described as the propert
arXiv:2609.38914v1 Announce Type: new Abstract: Evaluating interactive agents is expensive. Agent behavior is stochastic, so reliability must be measured over repeated trials, but failures are rare an
The common paradigm of reinforcement learning with verifiable rewards (RLVR) is to let agents make multiple attempts at a task, and optimize towards the successful ones. This becomes problematic in th