most citedA Survey on Recent Advances in Conversational Data Generation

5 citations · 5 across the 1 of their papers we have counts for

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5 papers

cs.CL20265 cited

A Survey on Recent Advances in Conversational Data Generation

Heydar Soudani, Roxana Petcu, Evangelos Kanoulas +1

Recent advancements in conversational systems have significantly enhanced human-machine interactions across various domains. However, training these systems is challenging due to t…

cs.IR2026

SubSearch: Intermediate Rewards for Unsupervised Guided Reasoning in Complex Retrieval

Roxana Petcu, Evangelos Kanoulas, Maarten de Rijke

Large language models (LLMs) are probabilistic in nature and perform more reliably when augmented with external information. As complex queries often require multi-step reasoning o…

cs.AI2025

Query Decomposition for RAG: Balancing Exploration-Exploitation

Roxana Petcu, Kenton Murray, Daniel Khashabi +4

Retrieval-augmented generation (RAG) systems address complex user requests by decomposing them into subqueries, retrieving potentially relevant documents for each, and then aggrega…

cs.CL2025

A Comprehensive Taxonomy of Negation for NLP and Neural Retrievers

Roxana Petcu, Samarth Bhargav, Maarten de Rijke +1

Understanding and solving complex reasoning tasks is vital for addressing the information needs of a user. Although dense neural models learn contextualised embeddings, they still…

cs.CL2025

Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs

Arian Askari, Roxana Petcu, Chuan Meng +4

Identifying user intents in information-seeking dialogs is crucial for a system to meet user's information needs. Intent prediction (IP) is challenging and demands sufficient dialo…