Knowledge catalogue
arXiv:2609.17929v1 Announce Type: new Abstract: Accurate seafloor mapping is essential for marine science, archaeology, and environmental monitoring. However, integrating data from different sensors,
arXiv:2609.18139v1 Announce Type: new Abstract: Cross-view object geo-localization (CVOGL) locates a target in satellite imagery using drone or street-view queries. Existing methods train separate det
arXiv:2603.06084v2 Announce Type: replace Abstract: Large language models have been widely used for robotic task planning, often taking advantage of representations such as Behavior Trees (BTs). Visio
arXiv:2609.17987v1 Announce Type: new Abstract: The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manuall
arXiv:2609.18441v1 Announce Type: cross Abstract: Discrete choice model specification is a time-consuming task in which modellers often specify and estimate multiple models while balancing goodness-of
arXiv:2609.19088v1 Announce Type: new Abstract: Large vision-language models have achieved remarkable progress in multi-modal understanding, yet their capabilities in educational settings remain insuf
arXiv:2609.17548v1 Announce Type: new Abstract: Myovox, from myo (muscle) and vox (voice), decodes open-vocabulary English text from 31-channel surface electromyography (sEMG) recorded from the muscle
arXiv:2603.09908v2 Announce Type: replace Abstract: Existing aerial-robotics benchmarks target vehicles from hundreds of grams to several kilograms and typically expose only high-level state data. The
arXiv:2609.17699v1 Announce Type: new Abstract: We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive
arXiv:2609.18891v1 Announce Type: cross Abstract: Neurological prognostication after cardiac arrest commonly relies on electroencephalography (EEG). However, EEG demands high clinical resources. Bedsi
arXiv:2512.09524v2 Announce Type: replace-cross Abstract: Neural decoding is fundamental to brain-computer interfaces, with growing applications in healthcare. Previous research has focused on leverag
new unredacted filings in the publishers (including my employer) vs OpenAI and Microsoft lawsuit Microsoft's Director of applied science calls LLM training 'an astonishing theft of unprecedented propo
arXiv:2609.18007v1 Announce Type: cross Abstract: Text-to-image generative models are widely used in professional and creative settings, yet how they represent gender across occupations -- and whether
arXiv:2609.17550v1 Announce Type: new Abstract: Language models frequently abandon correct answers when users push back. We study this in two small instruction-tuned models from different families, Qw
arXiv:2609.17825v1 Announce Type: new Abstract: Understanding how deep neural networks make decisions remains a fundamental challenge. We present NObSP (Nonlinear Oblique Subspace Projections), a fram
arXiv:2609.18898v1 Announce Type: new Abstract: Training-free weighted aggregation is widely used to lift 2D semantic features onto 3D Gaussians for open-vocabulary scene understanding, yet its theore
arXiv:2609.18084v1 Announce Type: cross Abstract: Fine-tuning a Vision-Language-Action (VLA) model for a new deployment environment is expensive, yet most methods apply uniform-capacity adapters to ev
arXiv:2609.17790v1 Announce Type: new Abstract: Pre-trained vision-language models (VLMs) exhibit strong cross-domain recognition performance even without additional training. However, this robustness
Nvidia Corp., Google LLC and software startup Emerald AI Inc. have formed an industry consortium to promote the construction of flexible data centers. The AI Energy Management Alliance, or AEMA, offic
Financial Times: NYT court filing: ChatGPT's head wrote that publishers face an “existential threat” and a Microsoft executive called AI training “an astonishing theft” — Lawyers say AI co-founder Gre
arXiv:2609.17890v1 Announce Type: new Abstract: Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead. Pruning can reduce this c
arXiv:2609.19145v1 Announce Type: cross Abstract: Two dominant tokenisation algorithms are used by modern language models: byte-pair encoding (BPE) and UnigramLM. These differ along two orthogonal axe
arXiv:2609.18432v1 Announce Type: new Abstract: Extensive occlusions in real-world scenarios pose challenges to gait recognition due to missing and noisy information, as well as body misalignment in p
Hello, I'm at the old pro plan. With the upcoming cloud model retirement of deepseek v4 0731 flash in mind because 4.1 is supposed to be more efficient while providing even better results I remembered
arXiv:2603.04284v2 Announce Type: replace Abstract: Autonomous robotic systems are increasingly deployed for mapping, monitoring, and inspection in complex and unstructured environments. However, most
arXiv:2609.18191v1 Announce Type: new Abstract: Agile quadrotor avoidance of fast-moving obstacles requires anticipating collisions and selecting feasible maneuvers within short reaction windows. Reli
arXiv:2604.05967v2 Announce Type: replace Abstract: Understanding how training shapes the geometry of recurrent network dynamics is a central problem in time-series modeling. We study the emergence of
arXiv:2609.18582v1 Announce Type: cross Abstract: Precise multi-camera tracking traditionally relies on rigorous 3D site calibration, yet this requirement is often operationally impossible in large-sc
arXiv:2609.17942v1 Announce Type: new Abstract: The problem of identifiability in linear parametric models (LPMs) whose nodes follow either an ordered logit model or a regular one-parameter exponentia
arXiv:2609.18998v1 Announce Type: cross Abstract: Multi-agent LLM systems are expected to be more reliable because agents can catch each other's mistakes. But peer pressure cuts both ways: the same co
arXiv:2609.17633v1 Announce Type: new Abstract: The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use mor
arXiv:2609.17709v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems typically employ fixed retriever and generator configurations across queries, despite substantial differe
arXiv:2609.18363v1 Announce Type: new Abstract: Online multi camera 3D tracking must maintain scene global identities across synchronized views, yet query-based trackers carry these identities only im
arXiv:2609.18031v1 Announce Type: new Abstract: Contact-rich physical human--robot interaction (pHRI) imposes time-varying demands associated with physical interaction, motor regulation, and physiolog
arXiv:2609.18599v1 Announce Type: cross Abstract: Monte Carlo Tree Search (MCTS) is a powerful framework for solving complex decision-making problems, yet it often relies on the assumption that the si
Open-weight artificial intelligence model developer Arcee AI Inc. said today it has raised an undisclosed amount of cash in a new funding round that lifts its valuation to more than 1 billion. The Ser
OpenAI Group PBC today launched Astra for Law, a version of its GPT-6 Astra model set up for legal research and drafting. Astra for Law is not a new model. The company has wrapped GPT-6 Astra in a leg
OpenAI: OpenAI launches Astra for Law, combining GPT-6 Astra with a legal search index and instructions for legal analysis and writing, initially for select law firms — Our most powerful model, config
OpenAI says AI can automate 80% of GDP. Today, with current models. So why hasn't it been automated yet? @swyx says the constraint is supply. Supply of chips and memory. Demand shot through the roof b
OpenAI Group PBC today disclosed six new “concerning” incidents involving artificial intelligence agents behaving badly again. The agents made up data, moved files onto the public internet without per
arXiv:2609.18117v1 Announce Type: new Abstract: Dexterous grasp synthesis has advanced rapidly in generating stable and physically plausible hand poses, but real-world manipulation requires grasps tha
arXiv:2412.00176v4 Announce Type: replace Abstract: We explore whether pre-training on datasets with paintings is necessary for a model to learn an artistic style with only a few examples. To investig
Over 2 years ago @sayashk and I wrote a detailed deconstruction of p(doom) and argued that its primary function is to launder vague, evidence-free intuitions and fears through a facade of quantificati
arXiv:2609.18605v1 Announce Type: cross Abstract: As corporate AI adoption continues to grow, enterprise-grade LLM agents are being deployed into sensitive contexts such as hiring, healthcare, and fin
arXiv:2602.15882v2 Announce Type: replace-cross Abstract: Robot manipulation uses temporal context to select actions and visual foresight to assess their consequences, yet dense representations of pas
arXiv:2609.18154v1 Announce Type: cross Abstract: We describe our system for LitTraceQA (GroundLM @ EMNLP 2026): given a research question, retrieve the relevant papers from a pool of 27,487, cite the
arXiv:2609.19143v1 Announce Type: cross Abstract: Intelligent systems that act in the world require image understanding that is both comprehensive and spatially grounded. Current vision-language model
arXiv:2609.18732v1 Announce Type: new Abstract: Humanoid robots can step over, squeeze past, and duck under obstacles, but learning to select and coordinate these behaviors from onboard perception rem
arXiv:2602.11220v2 Announce Type: replace-cross Abstract: Large language models are commonly adapted to downstream tasks through supervised fine-tuning (SFT), but substantial distribution mismatch bet
arXiv:2609.17560v1 Announce Type: cross Abstract: Every production model is updated, by retraining, fine-tuning, quantization, or a silent vendor swap, and each update risks being worse than what it r
arXiv:2505.23126v5 Announce Type: replace Abstract: Although many benchmarks evaluate the reasoning abilities of Large Language Models (LLMs) within domains such as mathematics, coding, or data wrangl
arXiv:2609.18329v2 Announce Type: new Abstract: Remote sensing recognition is often constrained by scarce observations of rare targets and costly annotations, making realistic synthetic augmentation p
arXiv:2609.18588v1 Announce Type: new Abstract: For distribution system operators, short-term load forecasting (STLF) supports congestion management, voltage control, and asset protection. Most existi
arXiv:2609.18120v1 Announce Type: cross Abstract: AI-driven penetration testing has been demonstrated with premium frontier models such as GPT-4, but the per-engagement token cost makes continuous, au
Perhaps the most important warning I ever issued was this, to the US Senate, May 2023: “A month after GPT-4 was released, OpenAI released ChatGPT plug-ins, which quickly led others to develop somethin
arXiv:2609.18861v1 Announce Type: new Abstract: Adaptive learning systems commonly formulate learning path planning as Exercise-Centric (EC) recommendation, where the next step is inferred from item-l
arXiv:2609.18082v1 Announce Type: cross Abstract: In this paper we tackle the problem of aligning LiDAR point clouds also known as the point cloud registration problem. We propose a new algorithm, PES
arXiv:2609.18863v1 Announce Type: new Abstract: Reliable prediction of crystallographic texture in laser powder bed fusion is critical for linking process conditions with anisotropic response and for
arXiv:2609.17635v1 Announce Type: new Abstract: City pedestrian counting systems now feed economic indicators, planning decisions and safety operations, yet the twins built on top of them treat the in
arXiv:2609.18025v1 Announce Type: cross Abstract: Strong chromospheric absorption lines such as Halpha 6562.8 A and Ca II 8542.1 A provide vital diagnostics of plasma dynamics and thermal structure in