# CFDA & CLIP at TREC iKAT 2025: Enhancing Personalized Conversational Search via Query Reformulation and Rank Fusion

arXiv: https://arxiv.org/abs/2509.15588 · HTML: https://mlsanity.com/paper/2509.15588/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 24 references that are in the map.
- First posted on arXiv 19 Sep 2025.

## Builds on (most cited first, 14 of 14)

- [Efficient Memory Management for Large Language Model Serving with PagedAttention](https://mlsanity.com/paper/2309.06180/) (2023)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization](https://mlsanity.com/paper/1912.08777/) (2019)
- [SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking](https://mlsanity.com/paper/2107.05720/) (2021)
- [LongT5: Efficient Text-To-Text Transformer for Long Sequences](https://mlsanity.com/paper/2112.07916/) (2021)
- [Open-Domain Question Answering Goes Conversational via Question Rewriting](https://mlsanity.com/paper/2010.04898/) (2020)
- [Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting](https://mlsanity.com/paper/2310.09716/) (2023)
- [TREC CAsT 2019: The Conversational Assistance Track Overview](https://mlsanity.com/paper/2003.13624/) (2020)
- [CHIQ: Contextual History Enhancement for Improving Query Rewriting in Conversational Search](https://mlsanity.com/paper/2406.05013/) (2024)
- [IterCQR: Iterative Conversational Query Reformulation with Retrieval Guidance](https://mlsanity.com/paper/2311.09820/) (2023)
- [TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistants](https://mlsanity.com/paper/2405.02637/) (2024)
- [TREC iKAT 2023: The Interactive Knowledge Assistance Track Overview](https://mlsanity.com/paper/2401.01330/) (2024)
- [Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search](https://mlsanity.com/paper/2407.20189/) (2024)
- [SCAI-QReCC Shared Task on Conversational Question Answering](https://mlsanity.com/paper/2201.11094/) (2022)

## Abstract (arXiv)

The 2025 TREC Interactive Knowledge Assistance Track (iKAT) featured both interactive and offline submission tasks. The former requires systems to operate under real-time constraints, making robustness and efficiency as important as accuracy, while the latter enables controlled evaluation of passage ranking and response generation with pre-defined datasets. To address this, we explored query rewriting and retrieval fusion as core strategies. We built our pipelines around Best-of-N selection and Reciprocal Rank Fusion (RRF) strategies to handle different submission tasks. Results show that reranking and fusion improve robustness while revealing trade-offs between effectiveness and efficiency across both tasks.