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Found 12 papers, 8 papers with code
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
Retrieval pipelines-an integral component of many machine learning systems-perform poorly in domains where documents are long (e. g., 10K tokens or more) and where identifying the relevant document requires synthesizing information across the entire text.
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
Evaluating retrieval-augmented generation (RAG) systems traditionally relies on hand annotations for input queries, passages to retrieve, and responses to generate.
PDFTriage: Question Answering over Long, Structured Documents
Representing such structured documents as plain text is incongruous with the user's mental model of these documents with rich structure.
UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers
Many information retrieval tasks require large labeled datasets for fine-tuning.
Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking
Neural information retrieval (IR) systems have progressed rapidly in recent years, in large part due to the release of publicly available benchmarking tasks.
Embedding Recycling for Language Models
Real-world applications of neural language models often involve running many different models over the same corpus.
ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
Neural information retrieval (IR) has greatly advanced search and other knowledge-intensive language tasks.
Ranked #6 on
Zero-shot Text Search
on BEIR
Quantifying the Impact of Human Capital, Job History, and Language Factors on Job Seniority with a Large-scale Analysis of Resumes
As job markets worldwide have become more competitive and applicant selection criteria have become more opaque, and different (and sometimes contradictory) information and advice is available for job seekers wishing to progress in their careers, it has never been more difficult to determine which factors in a r\'esum\'e most effectively help career progression.
EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models
The advent of larger machine learning (ML) models have improved state-of-the-art (SOTA) performance in various modeling tasks, ranging from computer vision to natural language.
Examining the Ordering of Rhetorical Strategies in Persuasive Requests
We find that specific (orderings of) strategies interact uniquely with a request's content to impact success rate, and thus the persuasiveness of a request.
Mapping Researchers with PeopleMap
Discovering research expertise at universities can be a difficult task.
PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language Processing
Discovering research expertise at institutions can be a difficult task.
