Knowledge catalogue
arXiv:2607.26513v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models rely mainly on 2D inputs, neglecting the rich object structural information and commonsense knowledge inhere
arXiv:2601.06300v2 Announce Type: replace Abstract: Clinical trial amendments frequently introduce delays, increased costs, and administrative burden, with eligibility criteria being the most commonly
arXiv:2607.26641v1 Announce Type: new Abstract: Identity document (ID) authentication relies on the structural integrity of complex, high-frequency security patterns. However, advanced Generative AI m
arXiv:2607.26432v1 Announce Type: new Abstract: Face anti-spoofing (FAS) is increasingly expected to provide not only bona fide/spoof decisions, but also attack semantics and image-grounded evidence f
arXiv:2607.26964v1 Announce Type: cross Abstract: We study feature bagging through the lens of algorithmic stability. Feature bagging is an ensemble strategy that aggregates base learners trained on r
arXiv:2607.26801v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative learning over decentralized data silos without centralizing raw data. However, heterogeneous local archite
arXiv:2607.26618v1 Announce Type: cross Abstract: Federated PEFT enables LLMs to collaboratively adapt to decentralized private data without sharing raw examples. However, task heterogeneity across cl
arXiv:2607.26607v1 Announce Type: cross Abstract: Few-shot Open-set audio classification requires classifying query samples from known classes with a few labeled support samples while rejecting query
arXiv:2607.27078v1 Announce Type: cross Abstract: In this paper, we formulate three communication tasks for empirical optimal transport: distributed coupling sampling, cost-evaluable coupling output,
arXiv:2607.26637v1 Announce Type: new Abstract: Deployed LLM agents increasingly keep their long-term memory as a filesystem: a directory tree of markdown files that the agent itself reads, writes, an
Finally a good paper testing if file-system based memory for LLM agents is worth it. First, what does this look like? Deployed agents keep long-term memory as a folder of markdown files they read and
arXiv:2411.17136v2 Announce Type: replace-cross Abstract: Realised volatility has become increasingly prominent in volatility forecasting due to its ability to capture intraday price fluctuations. Wit
arXiv:2607.26423v1 Announce Type: cross Abstract: As autonomous drone deployments scale from individual units to coordinated swarms, the human operator's role shifts from direct piloting to high-level
arXiv:2607.26278v1 Announce Type: new Abstract: It is common for two-dimensional embeddings of high-dimensional data to be read far beyond what they can support. Distances in and between clusters, the
arXiv:2607.26398v1 Announce Type: new Abstract: Diffusion and flow-based models benefit from simple regression losses, but inference incurs significant overhead because sampling requires integration.
For decades, we’ve dreamed of robots that can seamlessly step into our world and lend a hand. Today, we take a major stride toward making that dream a reality: Introducing Gemini Robotics 2 from @Goog
arXiv:2607.26820v1 Announce Type: new Abstract: As large language models (LLMs) evolve from standalone assistants into autonomous agents, ensuring their safety requires shifting beyond pointwise risk
arXiv:2607.26455v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in knowledge acquisition and reasoning, yet their ability to retain previously acquir
arXiv:2607.26993v1 Announce Type: new Abstract: Face presentation attack detection (PAD) remains challenging under cross-dataset evaluation, where domain shift degrades models trained on a single data
NVIDIA’s AI Red Team found common failure modes in enterprise AI agents: weak access controls, unrestricted code execution via tools, unprotected network egress, and exposure of plaintext secrets. The
arXiv:2607.26645v1 Announce Type: new Abstract: Existing point-based generative methods for outdoor scenes primarily focus on LiDAR-conditioned completion. During training, noisy point clouds are cons
arXiv:2607.26715v1 Announce Type: new Abstract: Existing supervised and unsupervised shadow removal methods often suffer from limited generalization due to the insufficient diversity of available trai
arXiv:2607.27110v1 Announce Type: new Abstract: Autoregressive video diffusion models enable real-time streaming video generation. However, errors introduced during self-rollout accumulate over long h
arXiv:2607.27196v1 Announce Type: new Abstract: We present a novel approach to regression tasks using classification which is motivated by the mechanism used by fruitflies to sense their environment.
arXiv:2607.26492v1 Announce Type: new Abstract: The Mass-Conserving Perceptron (MCP) establishes a modeling paradigm in which conceptual hydrologic models can be reformulated as physically constrained
arXiv:2607.26825v1 Announce Type: new Abstract: Large language models (LLMs) encode rich concept-like information, but represent it implicitly through distributed statistical associations rather than
arXiv:2607.26504v1 Announce Type: new Abstract: Many discrete reasoning tasks, such as code generation, are inherently non-causal: programmers move between high-level structure and local details, a pr
arXiv:2607.26921v1 Announce Type: new Abstract: YOLO-Pose models provide efficient keypoint localization, but do not quantify the associated spatial uncertainty. We introduce a lightweight post-hoc pr
arXiv:2607.26903v1 Announce Type: cross Abstract: The key bottleneck in embodied AI is not model architecture but data. Although billions of human manipulation videos exist online, robots cannot direc
arXiv:2607.26853v1 Announce Type: new Abstract: Human personality theories characterize traits not as isolated attributes captured by a single score, but as stable individual tendencies expressed thro
arXiv:2607.26542v1 Announce Type: new Abstract: Medical image segmentation heavily depends on labor-intensive and time-consuming pixel-level annotations. Eye tracking offers a cost-effective solution
arXiv:2607.26571v1 Announce Type: new Abstract: The operational energy consumption of large language model (LLM) inference is becoming an increasingly important component of the environmental footprin
arXiv:2607.26817v1 Announce Type: cross Abstract: Visual Floorplan Localization (FLoc) has emerged as a promising solution for indoor localization by matching egocentric images against minimalist stru
arXiv:2607.26521v1 Announce Type: new Abstract: Conventional subgroup analyses can yield unstable and difficult-to-interpret conclusions, especially in observational biomedical data where each individ
arXiv:2603.10046v2 Announce Type: replace Abstract: Wearable sensors in Internet of Things (IoT) ecosystems increasingly support applications such as remote health monitoring, elderly care, and smart
arXiv:2509.11594v3 Announce Type: replace Abstract: GBPP is a fast learning based scorer that selects a robot base pose for grasping from a single RGB-D snapshot. The method uses a two stage curriculu
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic app
arXiv:2607.26967v1 Announce Type: new Abstract: Emotion-cause pair extraction in conversation (ECPEC) identifies utterance pairs in which one utterance causes an emotion expressed in another. Recent L
arXiv:2607.26646v1 Announce Type: new Abstract: We address the problem of reconstructing a high-fidelity, freely navigable 3D scene from a single 360^irc panorama, without per-scene optimization or mu
arXiv:2607.19083v2 Announce Type: replace Abstract: Equivariant graph neural networks provide a powerful modeling language for three-dimensional scientific data, but their reuse is often limited by im
Hi all, I have not seen this model talked about here but it seems like baseten (inference provider on OpenRouter) merged the vision encoder from Kimi k2.6 into GLM 5.2. I think the lack of vision was
arXiv:2607.26442v1 Announce Type: cross Abstract: At parking speeds, the kinematic bicycle is the prevailing model for car-like vehicles. Yet, despite its wide use, stabilizing feedback laws for this
arXiv:2607.26717v1 Announce Type: cross Abstract: This work presents a comprehensive analysis and design of global sensitivity-based input shapers for a 3D Unmanned Aerial Vehicle-payload system, emph
goblin-level blog post Turns out GPT-5.6 Sol is actually SoTA on ARC-AGI-3. Just took two setting changes. You just have to allow it to reason and work over multiple context windows with the help of o
good job little bro After deployment, we applied GPT-5.6 Sol to advance the frontier of efficiency by making itself more efficient to run. The results: - 20% lower serving costs from production GPU ke
Alphabet Inc.’s artificial intelligence research lab today debuted a family of models optimized to power humanoid robots. Google DeepMind says that the Gemini Robotics 2 series enables multiple autono
Google DeepMind says the latest version of its Gemini Robotics AI model can 'control entire humanoid robots.' While the previous model focused on controlling a humanoid robot's upper body, Gemini Robo
Google announced Gemini Robotics 2.0 on July 30 2026, launching a family of three models that enhance robot dexterity, safety, and whole‑body intelligence for humanoid machinery. The publicly released
GPT-5.6 found optimizations that 'reduced end-to-end serving costs by 20%' for OpenAI to serve that model Presumably that's billions of dollars a month in savings at this point? Codex analysed product
arXiv:2607.26115v1 Announce Type: cross Abstract: We introduce extbf{GPT-Red}, an automated red-teaming agent that is trained to discover novel prompt injection attacks against frontier LLMs. The goal
arXiv:2607.27042v1 Announce Type: cross Abstract: Adaptive rounding methods such as GPTQ, or equivalently Babai's nearest plane algorithm, round a real matrix to integers under a quadratic metric. The
arXiv:2604.05175v2 Announce Type: replace-cross Abstract: We consider constrained ergodic resource optimization in wireless networks with graph-structured interference. We train a diffusion model poli
arXiv:2603.26807v2 Announce Type: replace-cross Abstract: The performance of language models is commonly limited by insufficient knowledge and constrained reasoning. Prior approaches such as Retrieval
arXiv:2607.26602v1 Announce Type: cross Abstract: The rapid development of the Internet of Everything (IoE) is accelerating the adoption of intelligent applications. However, the massive number of con
arXiv:2509.07260v5 Announce Type: replace-cross Abstract: Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ulti
arXiv:2607.26886v1 Announce Type: cross Abstract: When asked to describe a medical image that was never attached, frontier vision-language models do not abstain: they confabulate a diagnosis. We show
arXiv:2607.26498v1 Announce Type: new Abstract: We present HERMES (Hybrid Ensemble for Radiotherapy-target segmentation, Malignancy staging, and Event-free Survival), a single containerized algorithm
arXiv:2607.14117v2 Announce Type: replace Abstract: Cross-version differencing of scientific documents is essential in scholarly publishing and technical documentation, but remains challenging because
arXiv:2607.26283v1 Announce Type: new Abstract: Collaborative Perception (CP) improves autonomous systems' awareness of their surroundings by sharing sensor data, intermediate features, and detection
arXiv:2607.27106v1 Announce Type: new Abstract: Emergency Departments (EDs) are critical access points in healthcare systems, yet they face persistent pressure from unpredictable patient demand, seaso