Knowledge catalogue
arXiv:2609.18100v1 Announce Type: cross Abstract: Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve
arXiv:2609.18314v1 Announce Type: new Abstract: Loss spikes are recurrent instabilities in neural-network training and can arise from multiple mechanisms. For Adam in particular, macroscopic loss spik
arXiv:2609.18488v1 Announce Type: cross Abstract: Diffusion and flow-matching models are typically trained by corrupting data through independently sampled Gaussian noise. While simple and scalable, t
arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm
arXiv:2609.17564v1 Announce Type: new Abstract: Deploying retrieval-augmented generation (RAG) on commodity GPUs such as the NVIDIA T4 (16 GB VRAM) exposes a practical failure mode we call the Compres
arXiv:2609.17940v1 Announce Type: new Abstract: Sparse mixture-of-experts models route each token through a sequence of expert selections. We ask whether the immediately preceding selection adequately
arXiv:2609.18723v1 Announce Type: new Abstract: We introduce Mahalanobis-Ensemble Decoding (ME-Decoding), a novel Large Language Model (LLM) decoding framework that frames candidate token selection as
arXiv:2609.18306v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collecti
arXiv:2609.17562v1 Announce Type: cross Abstract: Hybrid Spiking Neural Network (SNN)-Artificial Neural Network (ANN) architectures combine the energy efficiency of SNNs with the superior detection ac
arXiv:2609.18881v1 Announce Type: new Abstract: First-person-view (FPV) teleoperation of aerial swarms requires an operator to coordinate collective translation, viewing direction, and formation spaci
arXiv:2505.01912v3 Announce Type: replace-cross Abstract: Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel
arXiv:2609.17892v1 Announce Type: cross Abstract: The manifold hypothesis suggests a natural criterion for clustering: partition data according to the manifold component from which each point is drawn
arXiv:2406.13668v4 Announce Type: replace Abstract: A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on t
arXiv:2609.18278v1 Announce Type: new Abstract: Artificial Intelligence (AI) is currently only applied to non-safety critical applications due to the strict standards and regulations for railway indus
arXiv:2609.18489v1 Announce Type: cross Abstract: This study analyses kinetic energy (KE) spectra, difference kinetic energy (DKE) spectra, and signatures of KE transfer across spatial scales in four
arXiv:2602.03994v3 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) prompting is widely used as a reasoning aid and is often treated as a transparency mechanism. Yet behavioral gains unde
Hey all, Henry from Cactus Compute here, I kinda wanted to share our latest model and get feedback from the family :) Needle 3 is a small foundation model for automation: you give it the functions you
arXiv:2609.18473v1 Announce Type: new Abstract: We present CADSplat, a framework that reconstructs photorealistic, geometrically accurate digital twins from sparse (<15 views), wide-baseline posed ima
arXiv:2609.18718v1 Announce Type: new Abstract: Retrieving a target from clutter requires deciding whether to grasp the target, remove a blocker, or defer. Existing methods typically commit to a singl
arXiv:2609.17820v1 Announce Type: new Abstract: Fine-grained recognition of visually similar industrial parts is challenging when classes differ primarily in physical dimensions. Normalizing detected
Yoyo I renamed https://github.com/syv-ai/qwen38-27b-rtx3090 to https://github.com/syv-ai/HyperQwen/ to focus more on Qwen models and 'local' hardware in general, than just a single card and a single m
arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety
arXiv:2609.18323v1 Announce Type: new Abstract: Recent Omni-Modal Generative Models (Omni-Models) have advanced content generation toward unified modeling of text, images, video, and audio. MiniMax-H3
arXiv:2609.17882v1 Announce Type: cross Abstract: An important component of urban accessibility, particularly for wheelchair users and people with reduced mobility, is sidewalk compliance with measura
arXiv:2609.18213v1 Announce Type: new Abstract: Robotic piano playing has emerged as a standard benchmark for dexterous bimanual manipulation, yet progress on it has been measured almost entirely by n
arXiv:2609.19000v1 Announce Type: new Abstract: Emergent capabilities are widely treated as unpredictable: loss improves smoothly while abilities appear abruptly. Prior work offers early-warning indic
arXiv:2609.18206v1 Announce Type: cross Abstract: The MUMU track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge requires a single unified multimodal model to jointly solve image ta
arXiv:2609.17688v1 Announce Type: new Abstract: Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token c
arXiv:2609.18554v1 Announce Type: new Abstract: Multiresolution hash encodings have recently enabled fast and high-fidelity implicit neural representations by storing multi-scale features in fixed-siz
arXiv:2609.18910v1 Announce Type: new Abstract: Conventional motion planning treats collision as a binary constraint, although contact with different objects can have drastically different consequence
arXiv:2412.11420v2 Announce Type: replace Abstract: Estimating the 6D pose and 3D size of an object from visual data is a fundamental task in computer vision. Although single-view geometry is a deeply
arXiv:2609.18016v1 Announce Type: new Abstract: World-action models (WAMs) have emerged as a promising paradigm for robot manipulation by jointly modeling future visual dynamics and robot actions. How
arXiv:2609.18779v1 Announce Type: new Abstract: Current Mixture-of-Agents (MoA) paradigms generally treat query routing and agent fine-tuning as separate processes, limiting their ability to respond t
arXiv:2609.18950v1 Announce Type: new Abstract: A robot's learned model of its own dynamics is only valid until those dynamics change: actuators wear, payloads shift, and joints stiffen. A model-based
arXiv:2609.18073v1 Announce Type: new Abstract: This work studies how refraction-induced bias on acoustic ranging affects multi-agent collaborative localization in a range of oceanographic conditions
arXiv:2609.18167v1 Announce Type: cross Abstract: Adapting to changes in robot dynamics requires learning from new data without discarding experience that may still be useful. In continual model-based
arXiv:2609.18051v1 Announce Type: new Abstract: Fresh-market blueberries require selective, gentle picking, which is labor-intensive and expensive. Over-the-row machine harvesters are fast but non-sel
Salut, je cherche de l'aide pour un projet d'IA locale. J'ai un Dell OptiPlex 7070 Micro sous ubuntu server avec un i5-9500T, 32 Go de RAM et aucun GPU (j'en ajouterai un à l'avenir). Je sais que la m
The revamped projects feature in Claude Code allows users to run multiple agents under the same roof, with a shared memory, goals, and library of files and artifacts. Similar to Grok Bot and other too
Why evaluating image editing models is both critical and challenging Instruction-based image editing is becoming a core capability of multimodal foundation models. Users can increasingly edit images s
arXiv:2609.18736v1 Announce Type: new Abstract: Despite recent advances in large language models (LLMs), performing logically consistent deductive reasoning over extended interactions remains challeng
arXiv:2609.18038v1 Announce Type: new Abstract: The world population is growing rapidly, and technology is improving in parallel. Meeting the huge demand for food for these 7 billion people not only d
arXiv:2609.19002v1 Announce Type: cross Abstract: Execution-based verification enhances large language models' mathematical reasoning through computational soundness and dependency-aware filtering. Ho
arXiv:2609.19128v1 Announce Type: new Abstract: Language agents remain brittle in interactive environments, where success requires long-horizon state tracking, valid action execution, and recovery fro
arXiv:2609.18131v1 Announce Type: cross Abstract: In this paper, we present a Mixture-of-Experts (MoE) quantization method based on activation entropy. Although quantization reduces memory and computa
arXiv:2609.17921v1 Announce Type: new Abstract: Vision-language model (VLM) agents combine specialized perception, tools, and reasoning to address complex visual tasks. In multi-agent settings, differ
arXiv:2609.18460v1 Announce Type: new Abstract: How does a multi-agent system evolve from a local deviation into collective loss of control? We propose an epidemic explanation organized around acciden
Come hang out with AI engineers, tech leads, and the Fireworks team during AI Engineer 2026. Want to leave with hands-on experience fine-tuning, evaluating, and deploying a model on Fireworks? Bring y
arXiv:2503.12018v2 Announce Type: replace-cross Abstract: Text-to-Image (T2I) diffusion models have made rapid progress on semantic alignment (generating what is described in the prompt), yet users st
arXiv:2609.18519v1 Announce Type: cross Abstract: With the rapid advancement of deep learning technology, shared GPU clusters receive an increasing number of deep learning training (DLT) jobs. Yet res
arXiv:2609.18996v1 Announce Type: new Abstract: LLM agents have repeatedly struggled to convert knowledge of a game into competent play, even when researchers build the agent around the model - supply
arXiv:2609.19004v1 Announce Type: cross Abstract: Code optimization plays a crucial role in the development of virtual machine compilers, with optimization frameworks significantly enhancing the perfo
arXiv:2609.17697v1 Announce Type: new Abstract: Integrated deep reinforcement learning (DRL) and model predictive control (MPC) methods are increasingly used to control autonomous systems by combining
arXiv:2609.18820v1 Announce Type: new Abstract: Agentic workflows now make consequential decisions in regulated settings, and the governance placed around them is almost entirely step-scoped: input-ou
arXiv:2609.18928v1 Announce Type: cross Abstract: In particle collider experiments, event reconstruction is the task of inferring the kinematics of short-lived particles produced in the hard scatter f
arXiv:2603.29732v2 Announce Type: replace Abstract: Single-pixel imaging (SPI) is a promising imaging modality with distinctive advantages in strongly perturbed environments. Existing SPI methods lack
arXiv:2609.17708v1 Announce Type: cross Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that
arXiv:2506.24048v2 Announce Type: replace-cross Abstract: Consensus-based optimization (CBO) has established itself as an efficient gradient-free optimization scheme, with attractive mathematical prop
arXiv:2508.08307v2 Announce Type: replace-cross Abstract: Machin-like arctangent relations are classical tools for computing pi, with efficiency quantified by the Lehmer measure (lambda). We present a
arXiv:2609.17983v1 Announce Type: new Abstract: KV-cache reuse can reduce inference cost in retrieval-augmented generation and agentic systems, but cached contexts may become stale when retrieved know