Hallucination is one of the most critical obstacles to reliably deploying Large Vision-Language Models (LVLMs): the model produces fluent, confident text that is factually inconsistent with what is ...
Abstract: The present portable communication devices need high speed data transmission to support different interfaces and display technologies. These communication devices transmit data between ...
Summary: Meta’s Fundamental AI Research team has unveiled TRIBE, a groundbreaking foundation model designed to predict how the human brain processes visual and auditory stimuli. Trained on massive ...
Deep learning models for decoding intracortical neural activity during attempted speech into text. This repository contains our team's implementation for the COMP 433 Fall 2025 course project, ...
Motivation In order to advance in the understanding of neuronal cultures as an alternative for in silico computers that could lead to a new generation of massivelly parallel biological neuroprocessors ...
Most clients can't read their cats. Tiffany Tupler, DVM, CBCC-KA, HABc, explains why this is a clinical problem and makes the case for using clinic visits to train clients in feline communication.
Abstract: In deep learning-based dehazing strategies, attention mechanisms are widely used to refine feature representations and improve overall performance. However, conventional contextual attention ...
The scaling of inference-time compute has become a primary driver for Large Language Model (LLM) performance, shifting architectural focus toward inference efficiency alongside model quality. While ...
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