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Articles: 9
Peer reviewed: 7
Open reports: 24

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Research ArticleUnder peer review

Dense Retrieval for Code-Mixed Queries: A study of Hindi–English and Yoruba–English search

Oluwaseun Adebayo, Elias Wagner, Ravi Menon

Version 1 · 0 reviewer reports · 5 October 2026 · 10.xxxx/ctm.pb.2026.0009

Users frequently mix languages within a single query, but retrieval benchmarks rarely reflect this. We construct code-mixed query sets for two language pairs and evaluate dense retrievers under different tokenisation and fine-tuning strategies. Adapting the query encoder with synthetic code-mixed data improves recall@20 by 9 points over a multilingual baseline, while transliteration normalisation helps for romanised queries but hurts for native-script queries.

Abstract PDF 640 1880 cited

Research ArticleUnder peer review

Quantisation-Aware Distillation for On-Device Assistants

Daniel Okafor, Yuki Saito, Priya Venkataraman

Version 1 · 1 reviewer report · 28 August 2026 · 10.xxxx/ctm.pb.2026.0006

Running assistant-grade language models on phones requires both small models and low-precision arithmetic, yet distillation and quantisation are usually applied one after the other. We train a 1.3B-parameter student with distillation losses computed through simulated 4-bit quantisation, so that the student learns to be robust to its own rounding error. Compared with distilling first and quantising afterwards, the joint procedure recovers 41% of the accuracy lost to 4-bit quantisation, reaches 94% of the full-precision student on a suite of assistant tasks, and runs 3.1× faster on a mid-range mobile processor.

Abstract PDF 2,144 7862 cited