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Found 7 papers, 1 papers with code
LLM-Generated Black-box Explanations Can Be Adversarially Helpful
Most LLMs are not able to find alternative paths along simple graphs, indicating that their misleading explanations aren't produced by only logical deductions using complex knowledge.
A Comparative and Experimental Study on Automatic Question Answering Systems and its Robustness against Word Jumbling
This helps us to be able to answer new questions accurately as long as it is a relevant question.
Question-focused Summarization by Decomposing Articles into Facts and Opinions and Retrieving Entities
This research focuses on utilizing natural language processing techniques to predict stock price fluctuations, with a specific interest in early detection of economic, political, social, and technological changes that can be leveraged for capturing market opportunities.
Hybrid Recommendation System using Graph Neural Network and BERT Embeddings
The hybridization of the GNN and transformer embeddings enables us to capture both inter-level and intra-level features of anime data. Our model not only recommends anime to users but also predicts the rating a specific user would give to an anime.
Hybrid Genetic Algorithm and Hill Climbing Optimization for the Neural Network
The genetic algorithm is used for selecting and breeding the fittest chromosomes to generate new offspring.
Multi-BERT for Embeddings for Recommendation System
We evaluate our model on a book recommendation task and demonstrate its effectiveness in generating more semantically rich and accurate document embeddings.
Automated ensemble method for pediatric brain tumor segmentation
Brain tumors remain a critical global health challenge, necessitating advancements in diagnostic techniques and treatment methodologies.
