Information Retrieval
862 papers with code • 10 benchmarks • 83 datasets
Information retrieval is the task of ranking a list of documents or search results in response to a query
( Image credit: sudhanshumittal )
Benchmarks
These leaderboards are used to track progress in Information Retrieval
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Libraries
Use these libraries to find Information Retrieval models and implementations
MS MARCO
BioASQ
CORD-19
PubLayNet
QASC
MTEB
MedleyDB
Subtasks
Latest papers with no code
Fine-tuning Pre-trained Named Entity Recognition Models For Indian Languages
We present a human annotated named entity corpora of 40K sentences for 4 Indian languages from two of the major Indian language families.
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems
To address this issue, we propose an improved ranking principle for multi-stage systems, namely the Generalized Probability Ranking Principle (GPRP), to emphasize both the selection bias in each stage of the system pipeline as well as the underlying interest of users.
LLMs Can Patch Up Missing Relevance Judgments in Evaluation
Based on our simulation experiments conducted on three TREC DL datasets, in the extreme scenario of retaining only 10% of judgments, our method achieves a Kendall tau correlation of 0. 87 and 0. 92 on an average for Vicu\~na-7B and GPT-3. 5 Turbo respectively.
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models
The reordering learning process is divided into two steps according to the quality of the generated responses: document order adjustment and document representation enhancement.
Comparative Analysis of Retrieval Systems in the Real World
This research paper presents a comprehensive analysis of integrating advanced language models with search and retrieval systems in the fields of information retrieval and natural language processing.
SUKHSANDESH: An Avatar Therapeutic Question Answering Platform for Sexual Education in Rural India
In this regard, we strive towards designing SUKHSANDESH, a multi-staged AI-based Question Answering platform for sexual education tailored to rural India, adhering to safety guardrails and regional language support.
"In-Context Learning" or: How I learned to stop worrying and love "Applied Information Retrieval"
With the increasing ability of large language models (LLMs), in-context learning (ICL) has evolved as a new paradigm for natural language processing (NLP), where instead of fine-tuning the parameters of an LLM specific to a downstream task with labeled examples, a small number of such examples is appended to a prompt instruction for controlling the decoder's generation process.
Question Suggestion for Conversational Shopping Assistants Using Product Metadata
Digital assistants have become ubiquitous in e-commerce applications, following the recent advancements in Information Retrieval (IR), Natural Language Processing (NLP) and Generative Artificial Intelligence (AI).
Integrating A.I. in Higher Education: Protocol for a Pilot Study with 'SAMCares: An Adaptive Learning Hub'
However, with all the diverse learning sources, it becomes harder for students to comprehend a large amount of knowledge in a short period of time.
Multi-hop Question Answering over Knowledge Graphs using Large Language Models
Knowledge graphs (KGs) are large datasets with specific structures representing large knowledge bases (KB) where each node represents a key entity and relations amongst them are typed edges.
