Page Stream Segmentation with LLMs: Challenges and Applications in Insurance Document Automation
Explores LLM applications for document processing automation in insurance, using parameter-efficient fine-tuning for page stream segmentation with …
Natural-Language-Processing
11 posts tagged with natural-language-processing.
Large Language Models for Page Stream Segmentation
Introduces the TABME++ benchmark and evaluates LLM performance on page stream segmentation, demonstrating superior performance of decoder-based models …
Sarcasm Detection with Transformers: When Perfect Accuracy Isn't Perfect
Learn how dataset bias can lead to misleading results in NLP: a sarcasm detection model that actually learned to classify news sources.
US Policy Area Classification Challenge
Machine learning models to classify congressional bills by policy area, achieving 87%+ accuracy through systematic analysis of legislative text and …
EigenNoise: A Contrastive Prior to Warm-Start Representations
Novel initialization scheme for word vectors based on dense co-occurrence modeling, achieving competitive performance with GloVe without requiring …
To Know by the Company Words Keep and What Else Lies in the Vicinity
Analytical model of statistics learned by Word2Vec and GloVe, deriving the first known solution to Word2Vec's softmax-optimized skip-gram algorithm …
The earth is flat and the sun is not a star: The susceptibility of GPT-2 to universal adversarial triggers
Examines universal adversarial triggers in natural language models, showing how specific text sequences can manipulate GPT-2's outputs on …
Latent semantic network induction in the context of linked example senses
Explores data-driven wordnet construction using Wiktionary, showing that semantic networks can be effectively induced from noisy, user-annotated …
CoQA Dataset: Advancing Conversational Question Answering
Explore CoQA: the conversational QA dataset that challenges AI with multi-turn dialogue, coreference resolution, and natural answers.
Count Vectorization with scikit-learn in Python
Learn about count vectorization in Python: from basic one-hot encoding to text preprocessing techniques with scikit-learn and real datasets.
Word Embeddings in NLP: An Introduction
Learn about word embeddings in NLP: from basic one-hot encoding to contextual models like ELMo. Guide with examples.