Detecting unknown deepfake manipulations remains one of the most challenging problems in face forgery detection. Current state-of-the-art approaches fail to gen...
We present VINO, a unified visual generator that performs image and video generation and editing within a single framework. Instead of relying on task-specific ...
In music creation, rapid prototyping is essential for exploring and refining ideas, yet existing generative tools often fall short when users require both struc...
We introduce Talk2Move, a reinforcement learning (RL) based diffusion framework for text-instructed spatial transformation of objects within scenes. Spatially m...
Farmers in remote areas need quick and reliable methods for identifying plant diseases, yet they often lack access to laboratories or high-performance computing...
This work introduces Falcon-H1R, a 7B-parameter reasoning-optimized model that establishes the feasibility of achieving competitive reasoning performance with s...
Companies regularly have to contend with multi-release systems, where several versions of the same software are in operation simultaneously. Question answering ...
Recent works propose extending 3DGS with semantic feature vectors for simultaneous semantic segmentation and image rendering. However, these methods often treat...
Toxicity detection is inherently subjective, shaped by the diverse perspectives and social priors of different demographic groups. While ``pluralistic'' modelin...
We present BEDS (Bayesian Emergent Dissipative Structures), a theoretical framework that unifies concepts from non-equilibrium thermodynamics, Bayesian inferenc...
This study explores the application of autoencoder-based machine learning techniques for anomaly detection to identify exoplanet atmospheres with unconventional...
Out-of-distribution (OOD) prediction is often approached by restricting models to causal or invariant covariates, avoiding non-causal spurious associations that...
Autoregressive language models typically use temperature parameter at inference to shape the probability distribution and control the randomness of the text gen...
Contactless fingerprint recognition offers a hygienic and convenient alternative to contact-based systems, enabling rapid acquisition without latent prints, pre...
Empirical evaluation serves as the primary compass guiding research progress in foundation models. Despite a large body of work focused on training frontier vis...
Geo-Foundation Models (GFMs), have proven effective in diverse downstream applications, including semantic segmentation, classification, and regression tasks. H...
As Large Language Model (LLM) agents are increasingly tasked with high-stakes autonomous decision-making, the transparency of their reasoning processes has beco...
Coding theory plays a crucial role in enabling reliable communication, storage, and computation. Classical approaches assume a worst-case adversarial model and ...
Training large language models requires distributing computation across many accelerators, yet practitioners select parallelism strategies (data, tensor, pipeli...
High-Frequency trading (HFT) environments are characterised by large volumes of limit order book (LOB) data, which is notoriously noisy and non-linear. Alpha de...
Monocular omnidirectional visual odometry (OVO) systems leverage 360-degree cameras to overcome field-of-view limitations of perspective VO systems. However, ex...
We propose a privacy-preserving method for sharing text data by sharing noisy versions of their transformer embeddings. It has been shown that hidden representa...
Mexico is a country with a large number of indigenous languages, among which the most widely spoken is Nawatl, with more than two million people currently speak...
The increasing production of waste, driven by population growth, has created challenges in managing and recycling materials effectively. Manual waste sorting is...
