Knowledge catalogue
arXiv:2509.22992v2 Announce Type: replace Abstract: As machine learning models continue to grow in size and complexity, efficient serving faces increasingly broad trade-offs spanning accuracy, latency
arXiv:2608.02192v1 Announce Type: new Abstract: Thermal imaging remains effective under adverse illumination, yet passive long-wave infrared (LWIR) measurements often lack fine texture. Existing therm
arXiv:2603.00025v3 Announce Type: replace Abstract: Direct Preference Optimization (DPO) is effective for offline alignment but poorly matched to ontology-driven structured prediction, where preferred
arXiv:2608.01400v1 Announce Type: new Abstract: Tabular foundation models, driven by in-context learning, have rapidly grown in quality and popularity. However, recent approaches with either cell-base
arXiv:2608.02079v1 Announce Type: new Abstract: In vision-aided navigation and visual-inertial odometry, the quality of triangulated three-dimensional feature positions is a fundamental prerequisite f
arXiv:2608.02056v1 Announce Type: new Abstract: Recent advances in proposal-free Video Moment Retrieval (VMR) have highlighted the effectiveness of Static Scene Graphs (SSGs). By modeling objects and
arXiv:2608.01834v1 Announce Type: new Abstract: Humanoid teleoperation for demonstration collection requires coordinated whole-body motion, continuous dexterous hand control, and viewpoint control. Ex
arXiv:2608.01975v1 Announce Type: cross Abstract: Large language model (LLM) inference has evolved from an offline workload into a continuously operated software service, yet root-cause analysis remai
arXiv:2608.00510v1 Announce Type: new Abstract: Reliable pelvic bone segmentation (PBS) from CT is essential for robot-assisted pelvic trauma surgery, yet deploying a source-trained model to a new hos
arXiv:2608.00559v1 Announce Type: new Abstract: AI-generated image detectors deployed in open-world environments inevitably face distribution shifts as new and stronger generative models continue to e
arXiv:2608.00916v1 Announce Type: cross Abstract: Modern reranking recipes---billion-scale cross-encoders, mixture-of-experts (MoE) backbones, and distillation against strong teachers---have outpaced
arXiv:2608.02050v1 Announce Type: new Abstract: Can a strictly local, iterated, weight-shared computation primitive support language modelling, and which of those three properties actually drives the
arXiv:2608.01839v1 Announce Type: new Abstract: Transcranial focused ultrasound (tFUS) requires accurate estimation of the intracranial acoustic field, which is distorted by skull-induced aberrations.
arXiv:2608.00356v1 Announce Type: new Abstract: The First AI Children Challenge aims to advance real-world applications of computer vision and AI in child healthcare, child education, and pediatrics.
arXiv:2608.00492v1 Announce Type: cross Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence
arXiv:2608.02588v1 Announce Type: cross Abstract: In [AS21], Axiotis and Sviridenko conjectured that the linear dependence on the restricted condition number in sparse convex optimization cannot be im
// The confidence cliff in self-improving autoresearch // Autoresearch loops are still quite brittle. Here is a nice paper offering some insights into why this might be happening. Self-improving autor
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Trump’s AI protectionism has come for robotics —James O’Donnel
arXiv:2403.14606v4 Announce Type: replace Abstract: Artificial intelligence has recently experienced remarkable advances, fueled by large models, vast datasets, accelerated hardware, and, last but not
arXiv:2608.01032v1 Announce Type: new Abstract: Training error is what we can observe on a training set; test error is the quantity we actually care about. We study linear regression with squared-erro
arXiv:2608.00391v1 Announce Type: new Abstract: Token skipping is a widely used training-free way to accelerate vision--language--action (VLA) models by bypassing computation for most visual tokens at
arXiv:2606.13993v2 Announce Type: replace Abstract: A crucial aspect of linguistic capability is the ability to trade off between stored representations and abstract knowledge: one must retrieve learn
arXiv:2608.01587v1 Announce Type: cross Abstract: Machine-learning benchmarks often pair a label that aggregates a long temporal horizon with input observed through one or a few short windows. Their a
arXiv:2608.00507v1 Announce Type: new Abstract: Perceptual narrowing---the developmental loss of non-native phoneme discrimination in the first year of life itep{werker1984}---is a canonical developme
arXiv:2608.00497v1 Announce Type: new Abstract: The suicide is a terrifying act of a person who is misled by his own mental state. This problem arises across many countries. Sadly, Russia also has qui
Mistral AI has released Shieldstral, a 3‑billion‑parameter open‑weight model for content safety that can run locally on device. It interprets plain‑language moderation queries and returns calibrated s
arXiv:2603.23561v4 Announce Type: replace-cross Abstract: In the realm of machine learning theory, to prevent unnatural coding schemes between teacher and learner, No-Clash Teaching Dimension was intr
arXiv:2608.02306v1 Announce Type: new Abstract: We introduce a mathematical framework for shape comparison based on mapping functions from the shape domain to a common reference domain. This Push-Forw
arXiv:2608.02138v1 Announce Type: new Abstract: Current speech translation systems, including SpeechLLMs, are trained on cleaned text and tend to strip disfluencies like filled pauses and false starts
Sam Sabin / Axios: The UK AISI says it observed a total of 19 instances where Mythos and GPT-5.6 Sol tried to hack people and companies during a routine cyber evaluation in July — The U.K. AI Security
arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a
arXiv:2608.01169v1 Announce Type: new Abstract: Streaming VideoLLMs process frames causally while visual tokens grow continuously, making compression essential for controlling prefilling latency and m
this is a really clean and unique ai tool that acts more like an extension of you took me 15 min to set up a custom ai voice assistant w/ it’s own # that also picks up my calls when my phone is off an
this post from 3 years ago and commercial LLMs *still* can’t play chess anywhere near as well serious players (except by calling external tools) When @GaryMarcus and others point out that GPT-4 is bad
arXiv:2608.00561v1 Announce Type: cross Abstract: Vision-language models (VLMs) process image patches and text tokens in a shared residual stream, but the local geometry through which the two modaliti
arXiv:2608.01724v1 Announce Type: new Abstract: Group conversations are fundamental to human collaboration, yet standard large language models (LLMs) still struggle with the complexities of multi-part
To date, finding a drug has been a process of guess & check… screening millions of molecules hoping one binds. @chaidiscovery is changing the paradigm… describe the molecule you want, and the model de
Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles. Beyond seeing, Alpamayo understands and reasons through the complex world - thinks before it acts. I
Together AI gives developers a high-throughput production path for running DeepSeek V4 Flash across coding, tool-use, and agentic workloads. Start building: https://www.together.ai/models/deepseek-v4-
arXiv:2608.02376v1 Announce Type: cross Abstract: Search and database engines still store text as UTF-8, a format built for humans. But the systems that increasingly read and write that text (embedder
arXiv:2608.02504v1 Announce Type: new Abstract: Video Diffusion Transformers (VDiTs) enable high-fidelity generation but incur quadratic cost from dense 3D self-attention. Existing head- and block-lev
arXiv:2608.02080v1 Announce Type: new Abstract: Whole-body tactile sensing is a prerequisite for humanoids that operate in contact-rich human environments, but conventional taxel arrays scale poorly w
arXiv:2608.01743v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central paradigm for large language model (LLM) post-training, but optimization toward new objectives can deg
arXiv:2603.08091v2 Announce Type: replace Abstract: Large language model (LLM)-based judges are widely adopted for automated evaluation and reward modeling, yet their judgments are often affected by j
arXiv:2604.03422v2 Announce Type: replace Abstract: All languages have a noun category, but its realisation varies considerably. Depending on the language, semantic and/or morphosyntactic differences
arXiv:2606.18621v2 Announce Type: replace Abstract: Relational databases are widely used for managing structured data in real-world systems. Detecting anomalies from such relational data is crucial fo
arXiv:2608.01488v1 Announce Type: new Abstract: Unified multimodal object tracking has achieved remarkable robustness by leveraging complementary sensor data (e.g., RGB, Thermal, Depth), yet the heavy
arXiv:2608.00623v1 Announce Type: new Abstract: Multimodal-attributed graphs (MAGs), where nodes carry heterogeneous semantic content across multiple modalities while edges encode relational dependenc
arXiv:2608.00315v1 Announce Type: cross Abstract: Robot policies are becoming increasingly general, with vision-language-action (VLA) models enabling a single policy to execute diverse tasks specified
arXiv:2608.02304v1 Announce Type: new Abstract: Existing active reconstruction systems with Gaussian-splatting maps select observations greedily, optimizing a single next-best-view (NBV) at each step
arXiv:2608.00200v1 Announce Type: cross Abstract: Wearable sensors capture fine-grained motion patterns that support rich behavioral understanding, yet most existing methods reduce these signals to ac
arXiv:2608.00113v1 Announce Type: new Abstract: In Formula 1, drivers optimize racing lines within tire grip limits to minimize lap times; however, in rally racing, drivers intentionally break tractio
arXiv:2505.09710v4 Announce Type: replace Abstract: We investigate deep morphological neural networks (DMNNs), studying how changes in algebraic structure affect the expressivity and trainability of d
arXiv:2608.01407v1 Announce Type: new Abstract: Safe deployment of AI methods in medicine requires robust guardrails that detect when input data deviate from the training distribution to ensure that m
arXiv:2608.02415v1 Announce Type: new Abstract: Intent classification in Large Language Models (LLMs) involves categorizing user prompts into predefined classes. For instance, given a user prompt, the
arXiv:2608.01284v1 Announce Type: new Abstract: The normalized Transformer (nGPT) realizes hyperspherical representation learning by constraining model parameter vectors and activation vectors to the
arXiv:2608.01425v1 Announce Type: cross Abstract: Training LLM-based multi-agent systems with multi-agent reinforcement learning is rapidly gaining traction, and a parallel line of work argues that su
arXiv:2608.02302v1 Announce Type: cross Abstract: Long-horizon coding-agent trajectories are poorly matched to the credit units available to train on: a single action has no stable value, an episode l
arXiv:2608.01922v1 Announce Type: new Abstract: Multimodal Large Reasoning Models (MLRMs) have achieved strong performance on tasks requiring visual understanding and multi-step inference. However, as
arXiv:2502.11331v4 Announce Type: replace-cross Abstract: The proliferation of data has sparked significant interest in leveraging findings from one study to estimate treatment effects in a different