Knowledge catalogue
arXiv:2204.06142v2 Announce Type: replace-cross Abstract: Institutions of higher learning, research institutes and other scientific research units have abundant scientific and technological resources
arXiv:2607.08384v1 Announce Type: cross Abstract: We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints. We identify the phenome
arXiv:2603.01119v2 Announce Type: replace-cross Abstract: A fundamental challenge in causal inference with observational data is correct specification of a causal model. When there is model uncertaint
arXiv:2603.23318v2 Announce Type: replace Abstract: Among the different possible strategies for evaluating the reliability of individual predictions of classifiers, robustness quantification stands ou
arXiv:2607.08020v1 Announce Type: new Abstract: Autoregressive video diffusion enables efficient streaming and long-horizon video generation, but repeatedly reusing generated latents as causal context
arXiv:2607.08688v1 Announce Type: new Abstract: Modern Video Object Segmentation (VOS) involves tracking and segmenting user-specified targets. While recent approaches have achieved remarkable perform
arXiv:2607.08757v1 Announce Type: cross Abstract: Score matching controls average error under the forward marginals, but a discretized reverse-time sampler evaluates the learned score along its own tr
arXiv:2607.07748v1 Announce Type: new Abstract: Large Language Models achieve strong code generation for high resource languages like Python and Java but suffer sharp performance drops on Low-Resource
arXiv:2602.12612v2 Announce Type: replace-cross Abstract: Traditional methods for automating recommender system design, such as Neural Architecture Search (NAS), are often constrained by a fixed searc
arXiv:2311.00296v2 Announce Type: replace Abstract: Because most scientific literature data are unlabeled, semantic representation learning based on unsupervised graphs has become crucial. To enrich s
arXiv:2607.08573v1 Announce Type: new Abstract: Multimodal emotion and sentiment recognition is commonly addressed by early fusion, which concatenates modalities before classification, or late fusion,
arXiv:2607.07725v1 Announce Type: cross Abstract: Genomic prediction models often fail to transfer across institutions because sequencing panels differ across sites, creating structural feature missin
arXiv:2603.08311v2 Announce Type: replace-cross Abstract: We study identifiability in continuous-time linear stationary stochastic differential equations with a known causal structure. Unlike existing
arXiv:2607.08340v1 Announce Type: cross Abstract: Q-learning is a fundamental algorithm in reinforcement learning (RL) for solving discounted Markov decision processes (MDPs) when the transition kerne
arXiv:2607.08581v1 Announce Type: new Abstract: Extreme Learning Machine (ELM) computes output weights analytically using the Moore-Penrose pseudoinverse. Although this leads to fast training, its num
Ties van der Meer doesn’t know how many siblings he has. The 47-year-old was conceived at a private fertility clinic in the Netherlands using sperm provided by an anonymous donor. After the Netherland
arXiv:2607.07996v1 Announce Type: cross Abstract: Continuous oxygen saturation (SpO_2) estimation from wearable photoplethysmography (PPG) is important for long-term health monitoring, but low-quality
arXiv:2603.23571v2 Announce Type: replace-cross Abstract: Effective navigation intelligence relies on long-term memory to support both immediate generalization and sustained adaptation. However, exist
arXiv:2312.15341v1 Announce Type: cross Abstract: We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse
arXiv:2607.08103v1 Announce Type: new Abstract: Rank estimation under label noise poses a fundamental challenge, as ordinal annotations often exhibit structured uncertainty rather than simple label co
arXiv:2607.08522v1 Announce Type: new Abstract: The inherent rigidity of fixed-size benchmarks makes them an inefficient tool for model evaluation. Diverse evaluation objectives, including model ranki
arXiv:2607.08545v1 Announce Type: cross Abstract: End-to-end neural audio models achieve high-fidelity compression and generation. We might read that performance as evidence they directly represent in
arXiv:2607.08511v1 Announce Type: cross Abstract: Choosing a learning rate scheduling strategy is critical to neural network training, but manual selection is costly and rarely exhaustive. While class
Nous Research appears to be announcing an upcoming countdown or launch event, likely related to a project or product indicated by the carrot and wings emojis. Without access to the specific post conte
The Hermes Desktop app can now discover and connect to your Hermes Cloud agents. Sign in with Nous Portal and any active Cloud instances are auto-discovered. http://portal.nousresearch.com/cloud Media
arXiv:2607.07756v1 Announce Type: new Abstract: Multimodal learning usually requires a dedicated encoder per modality. When a tabular modality is involved, prior work has been mostly using a plain MLP
arXiv:2607.07944v1 Announce Type: cross Abstract: As Green Software Engineering matures, energy efficiency has transitioned into a mission-critical non-functional requirement. While software design pa
Today, together with @kyutai_labs, we’re introducing our new Audio-to-MIDI model. It takes a finished recording, identifies the instruments playing, and returns separate MIDI tracks for each — voice,
arXiv:2505.10946v3 Announce Type: replace-cross Abstract: Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units
arXiv:2607.08057v1 Announce Type: cross Abstract: Despite the rapid advancements of large language models (LLMs), LLM serving systems remain memory-intensive and costly. The key-value (KV) cache, whic
arXiv:2607.08393v1 Announce Type: new Abstract: Fine-tuning LLMs to inject new knowledge faces a critical challenge: LLMs can quickly memorize new facts, yet fail to use them for downstream reasoning
arXiv:2607.07958v1 Announce Type: new Abstract: Hand spasticity and resulting pain affect 12 million people worldwide, including stroke survivors, arthritis patients, and those with other muscle and n
arXiv:2607.08408v1 Announce Type: cross Abstract: Gaussian splatting is the current state-of-the-art for dense, deformable 3D anatomy reconstruction in robot-assisted minimally invasive surgery (RAMIS
arXiv:2511.15060v2 Announce Type: replace-cross Abstract: Total variation (TV) regularization is a classical edge-preserving technique widely used across image recovery and reconstruction problems; ho
arXiv:2602.01385v2 Announce Type: replace Abstract: Triphibious robots capable of multi-domain motion and cross-domain transitions are promising to handle complex tasks across diverse environments. Ho
arXiv:2602.23440v4 Announce Type: replace Abstract: Reinforcement learning has emerged as an effective paradigm for training large language models to interleave reasoning with search engine calls. How
arXiv:2607.08370v1 Announce Type: cross Abstract: We derive bounds for the volume of tubular neighbourhoods of smooth Pfaffian hypersurfaces, generalising known results for algebraic varieties. The bo
arXiv:2607.08339v1 Announce Type: cross Abstract: State-of-the-art code models achieve impressive performance, yet the extent to which they internally encode type information remains poorly understood
Typical NYT understatement for what is an apocalyptic destruction of the American innovation ecosystem. I can't understand how the Trump administration is doing this while boasting about American tech
arXiv:2607.08170v1 Announce Type: new Abstract: Zero-shot model size interpolation aims to create new models of intermediate target sizes by combining existing models without additional training. Rece
arXiv:2607.08007v1 Announce Type: cross Abstract: Galvanic skin response (GSR) is widely used for stress detection, but wrist-based GSR remains challenging because its absolute amplitude can differ su
arXiv:2607.07763v1 Announce Type: new Abstract: World models are typically trained to predict discrete-time physical dynamics with a fixed step size baked into the model weights, preventing prediction
arXiv:2607.07772v1 Announce Type: new Abstract: In this age of social media, sites like Twitter have become meeting places for people to share their views and feelings on a wide range of issues and cu
arXiv:2508.09767v3 Announce Type: replace-cross Abstract: We propose UtterTune, a lightweight method for adapting a multilingual text-to-speech (TTS) system built on a large language model (LLM). It i
arXiv:2607.08104v1 Announce Type: new Abstract: Stochastic gradient descent (SGD) is a cornerstone of modern optimization. While its performance under heavy-tailed noise is often addressed through spe
arXiv:2607.08489v1 Announce Type: cross Abstract: Vision-language models excel at video captioning, yet typically generate descriptions that fail to capture individual viewers' attention. We propose V
arXiv:2511.20644v2 Announce Type: replace Abstract: Spatial reasoning is a critical capability for intelligent robots, yet current vision-language models (VLMs) still fall short of human-level perform
arXiv:2607.08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories. Although recent vision-language and
arXiv:2607.08772v1 Announce Type: new Abstract: Estimating 3D geometry in underwater environments presents unique challenges due to light attenuation, scattering, and the absence of large-scale, high-
We're releasing MuScriptor, the best open model for multi-instrument transcription to date, created in collaboration with @MireloAI. Give it a recording in any genre: pop, classical, metal, jazz, what
arXiv:2607.08537v1 Announce Type: new Abstract: The recently established 'Out of Sight, Not out of Mind' (OSNOM) task for egocentric videos focuses on tracking objects that are moved by the camera wea
What do we do at @thinkymachines: Personalization/sovereignty, Human Participation, Decentralization. Democratize AI and make it useful for people. All three of them reduce society's dependence on cen
arXiv:2607.08046v1 Announce Type: cross Abstract: Large language models fine-tuned for forecasting can be accurate yet poorly calibrated, and their chain-of-thought (CoT) reasoning may not faithfully
arXiv:2607.07937v1 Announce Type: new Abstract: Preprocessing-based methods for stereotype mitigation, such as pre-/post-training on debiased corpora, are widely used in NLP. While these approaches re
arXiv:2607.07976v1 Announce Type: cross Abstract: Reinforcement learning (RL) has achieved remarkable success in enhancing the reasoning capabilities of large language models (LLMs). However, widely u
arXiv:2607.08265v1 Announce Type: new Abstract: Steering Cable-Driven Parallel Robots (CDPRs) beyond their Wrench-Feasible Workspace (WFW) augments their capabilities in challenging scenarios such as
arXiv:2607.08771v1 Announce Type: new Abstract: Monocular depth estimation has seen remarkable progress through foundation models achieving robust zero-shot generalization, yet their computational dem
arXiv:2607.06726v1 Announce Type: new Abstract: Faithful visual attribution identifies which image regions support a model prediction. Search-based perturbation methods lead the insertion--deletion fa
arXiv:2607.06802v1 Announce Type: cross Abstract: Open physiological corpora are heterogeneous: they use different sensors, labels, sampling rates, recording settings, and clinical endpoints. They can
arXiv:2607.07527v1 Announce Type: cross Abstract: Artificial intelligence (AI) is a double-edged sword: while it has achieved remarkable success across a wide range of domains, its deployment also cal