Efficient and Scalable Estimation of Tool Representations in Vector Space

Finetuning the DeBERTa v3 model for the emotion recognition task

Detect or classify input sentences as grammatically correct or incorrect by fine-tuning pre-trained DeBERTa-v3 model

Official repository for the EMNLP 2024 paper "How Hard is this Test Set? NLI Characterization by Exploiting Training Dynamics"

Application for training the pretrained transformer model DeBERTaV3 on an Aspect Based Sentiment Analysis task

Finding the source code hidden in the text.

Challenge to distinguish whether a sentence from a news article expresses the subjective view of the author behind it or presents an objective view on the covered topic

Split-based Prompt Injection Detector

Educational workshop for NLP engineers. Fine-tuning DeBERTa-v3 for CEFR level prediction on serverless Modal GPUs.

Submodular Subset Selection for Long-Document Question Answering

Backbone: 5 x DeBerta and Head: Rapids SVR

Real-time prompt injection defense at the edge. A zero-trust Chrome extension and local AI backend that intercepts cognitive threats before they reach your LLMs.

Tactical next-action + reasoning prediction on 348 football match contexts (Shipd Project Eris). 4-component ensemble with task-coupling: DeBERTa-v3-base / large, cross-encoder MCQ scorer, zero-shot NLI, and a three-pass Qwen3.5-35B-A3B-Int4 + Gemma-4-26B-A4B-it MoE fusion with PRM rerank. W&B-instrumented. Target combined ≥ 0.80

This repo details code for building a text classifier for predicting Bank Transaction categories. I finetune a base version of a DeBERTaV3 model purely on text data, as well as another version using a combination of text and non-text (e.g., categorical, datetime, etc.) data.

IELTS Automated Essay Scoring (AES) – Multi-Task DeBERTa-based Architecture

O Hybrid LLM Text Detection é um projeto de estudo e experimentação em Machine Learning e Processamento de Linguagem Natural (NLP) voltado para a identificação de textos gerados por modelos de linguagem. O projeto foi inspirado na competição do Kaggle LLM - Detect AI Generated Text.

A generative AI project that builds a self-improving reasoning agent using multiple AI models and agentic workflows. The system generates answers to complex tasks, evaluates its own reasoning through a critic model, and refines responses iteratively to produce more reliable outputs.

live trader utilizing DeBERTa to estimate sentiment off Polygon API data

ViBERTa is a fine-tuned DeBERTa model for sentiment analysis of McDonald's customer reviews, classifying sentiments as positive, negative, or neutral.