Applied

Contradiction retrieval refers to identifying and extracting documents that explicitly disagree with or refute the content of a query, which is important to many downstream applications like fact...

Contradiction detection is a task to recognize contradiction relations between a pair of sentences. Despite the effectiveness of traditional context-based word embedding learning algorithms in many natural language processing tasks, such algorithms are not powerful enough for contradiction detection. Contrasting words such as “overfull” and “empty” are mostly mapped into close vectors in such embedding space. To solve this problem, we develop a tailored neural network to learn contradiction-specific word embedding (CWE). The method can separate antonyms in the opposite ends of a spectrum. CWE is learned from a training corpus which is automatically generated from the paraphrase database, and is naturally applied as features to carry out contradiction detection in SemEval 2014 benchmark dataset. Experimental results show that CWE outperforms traditional context-based word embedding in contradiction detection. The proposed model for contradiction detection performs comparably with the top-performing system in accuracy of three-category classification and enhances the accuracy from 75.97% to 82.08% in the contradiction category.

Full Stack application for retrieving Stock Data and News using LLM, LangChain and LangGraph - vinay-gatech/stocks-insights-ai-agent

Compare performance, cost, and accuracy of leading Vision Language Models including GPT-4V, Claude 3.5, and open-source alternatives. Real-world testing on document processing tasks.

We investigate whether large language models (LLMs) can successfully perform financial statement analysis in a way similar to a professional human analyst

PaSa -- an advanced paper search agent powered by large language models. It can autonomously make a series of decisions, including invoking search tools, reading papers, and selecting relevant refe...

Cosine similarity - the duct tape of AI. Convenient but often misused. Let's find out how to use it better.

This paper describes an efficiently scaleable approach to measuring technological similarity between patents by combining embedding techniques from na…

What are the advantages of Triplet Loss over Contrastive loss and how to efficiently implement it?

Python tool for converting files and office documents to Markdown. - microsoft/markitdown

PyMuPDF is a high-performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents.

Extract any data from any document. Resumes, invoices, contracts, academic research, bank statements, utility bills and more – Sensible can parse them all.

The document processing platform built for the next generation.

Reducto is an API that provides high quality data ingestion for large language models (LLMs). It works with any vector database or embedding system. It can parse PDFs, Excel, PowerPoint, and more.

A system for agentic LLM-powered data processing and ETL - ucbepic/docetl

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

The release of BERT revolutionized natural language processing (NLP), setting a new standard for encoder-only transformer models. However…

A Blog post by David Berenstein on Hugging Face

Modern updated guide on how to fine-tune BERT models for classification tasks in 2025.

An AI Hedge Fund Team. Contribute to virattt/ai-hedge-fund development by creating an account on GitHub.

If you’ve followed the news around the intersection of AI and the legal field recently, you might have heard about a lawyer who cited…

But what exactly are MoEs? 🤔 A Mixture of Experts (MoE) is a machine learning framework that resembles a team of specialists, each adept at handling different aspects of a complex task. It's like… — Akshay 🚀 (@akshay_pachaar)

Ironclad's contract AI technology helps businesses do more with contracts – work faster, collaborate effectively, and make better decisions.

For “R”, our DSE dropped the document processing and improved relevancy modeling by preserving the content integration. Now for “G”, we propose VISA. Aiming to take a step towards more verifiable and intuitive V-RAG.… — Xueguang Ma (@xueguang_ma)

— Jo Kristian Bergum (@jobergum)

LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.

I made a tutorial showing you how to build a contract review agentic workflow - given a vendor agreement, parse it into a set of key clauses, match it with relevant clauses from a set of guidelines (GDPR),… — Jerry Liu (@jerryjliu0)