Information Retrieval
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Benchmarks
BSARD
MS MARCO
CQADupStack
MTEB
TREC-PM
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Amazon
MSLR-WEB30K
MSMARCO
News Headlines
Ohsumed
Most implemented
Modeling Relational Data with Graph Convolutional Networks
TransferTransfo: A Transfer Learning Approach for Neural Network Based Conversational Agents
CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
Declarative Experimentation in Information Retrieval using PyTerrier
Papers
Shadow Queries for Private Retrieval in Vector Databases
Large language models (LLMs) increasingly rely on information retrieval (IR) systems, such as Retrieval-Augmented Generation (RAG), to incorporate domain-specific knowledge without costly re-training. These systems often…
Information RetrievalLearning to Reason and Use Tools through Unsupervised Fine-Tuning in Task-Oriented Dialog Systems
Current dialogue systems struggle with dynamic information retrieval, often leading to hallucinations and lower response accuracy. We address this by adapting the ReAct framework for Task-Oriented Dialogue, enabling Larg…
Domain GeneralizationInformation RetrievalMULTI3IR: A Benchmark for Multi-perspective Multi-domain Multi-modal Information Retrieval
Information retrieval (IR) increasingly targets open-ended queries that admit diverse perspectives. Existing IR benchmarks, however, focus primarily on closed-ended queries, while even open-ended benchmarks largely consi…
Information RetrievalData Citation for Large Language Models: A Challenge
Large language models increasingly mediate access to information, and a growing body of work asks whether they cite the sources behind their outputs. That work treats citation as a verification device and applies it to t…
Information RetrievalAgentWorld: Personality-Aware Reliability Evaluation for Agentic Information Retrieval
Evaluation of agentic information retrieval remains limited to scripted interactions with uniform users, missing both natural personality diversity and adversarial brittleness. We present AgentWorld, a simulation framewo…
Information RetrievalRobustness of IR Models to Collection Growth
Information Retrieval (IR) systems seek to identify relevant documents within a collection. In practical applications, collections are dynamic, with documents frequently added. We argue that ideally, a retriever's effect…
Information Retrieval