arXiv Computation and Language
TSWAP: A Multilingual Retrieval-Augmented Thai Wellness Advisor
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MMed-Bench-IR: A Heterogeneous Benchmark for Multilingual Medical Information Retrieval
arXiv:2606. 24200v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) in clinical settings increasingly requires multilingual retrieval against predominantly English evidence corpora.
arXiv AI
Aug 13
A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench
arXiv:2608. 12138v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but such comparisons draw on a narrow set of systems and on benchmarks developed largely in high-income settings.
arXiv AI
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KSE-Web: An Analysis of Hybrid Retrieval and LLM-Assisted Query Expansion for Low-Resource Khmer Semantic Search
arXiv:2608.21365v1 Announce Type: cross Abstract: As a low-resource language, Khmer presents several retrieval challenges, including limited annotated data, ambiguous word boundaries, weak support in...
arXiv Computation and Language
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Efficient LLM Distillation for Bangladesh Legal Context: A Smartphone-Compatible Retrieval-Augmented Generation Model
The paper presents a smartphone‑compatible, retrieval‑augmented language model tailored to Bangladeshi statutory law. By distilling a 9‑billion‑parameter Gemma‑2 teacher into a 2‑billion‑parameter student using supervised fine‑tuning and QLoRA, the authors achieve significant gains in ROUGE‑L and BERTScore on an English benchmark while keeping the model lightweight (1.6 GB) and operable offline on a Pixel 6. The system retrieves from 36,029 statutory passages using a hybrid dense/BM25 approach, and cross‑lingual evaluation shows effective Bangla query handling against an English‑only corpus, with a practicing lawyer rating the responses highly in a pilot study.
arXiv Computation and Language
Sep 24
Automated Extraction of Records of Processing Activities (RoPA) Using Hybrid RAG and Locally Deployed Large Language Models
The paper introduces RoPA Manager, a system that automates the extraction of Records of Processing Activities (RoPA) required by Vietnam’s new Personal Data Protection Law. It combines hybrid retrieval techniques—lexical ranking, dense‑vector search, and Reciprocal Rank Fusion—with locally deployed large language models to avoid data‑sovereignty issues. A Vietnamese RoPA benchmark of 32 organizations and 77 processing activities was created, and the system achieved robust scorer performance (F1 ≈ 0.95) and moderate end‑to‑end token coverage (≈ 50‑55%).
Hugging Face Trending Papers
Jul 21
RAGAL: A Frugal, Fully Local Retrieval-Augmented Assistant for Technical Support at a Government Agency
Public institutions hold large volumes of sensitive documents and support tickets that cannot leave the premises, ruling out cloud-hosted language models entirely. We report on RAGAL, a retrieval-augmented assistant for the technical-support team of AFIR, the Romanian Agency for Financing Rural Investments, built and operated under three hard constraints: zero data egress (no external API calls, even for synthetic data), a read-only mandate (the assistant drafts, humans execute), and a single 8 GB consumer laptop as the only development and training machine.