- Blinded Radiologist and LLM-Based Evaluation of LLM-Generated Japanese Translations of Chest CT Reports: Comparative Study
Yosuke Yamagishi, Atsushi Takamatsu, Yasunori Hamaguchi, Tomohiro Kikuchi, Shouhei Hanaoka · Apr 2, 2026 · Citations: 0
Pairwise Preference Llm As JudgeAutomatic Metrics
A board-certified radiologist and a radiology resident independently performed blinded pairwise evaluations across 4 criteria: terminology accuracy, readability, overall quality, and radiologist-style authenticity.
- MENLO: From Preferences to Proficiency -- Evaluating and Modeling Native-like Quality Across 47 Languages
Chenxi Whitehouse, Sebastian Ruder, Tony Lin, Oksana Kurylo, Haruka Takagi · Sep 30, 2025 · Citations: 0
Pairwise PreferenceRubric Rating Automatic Metrics
To address this, we introduce MENLO, a framework that operationalizes the evaluation of native-like response quality based on audience design-inspired mechanisms.
- Do Compact SSL Backbones Matter for Audio Deepfake Detection? A Controlled Study with RAPTOR
Ajinkya Kulkarni, Sandipana Dowerah, Atharva Kulkarni, Tanel Alumäe, Mathew Magimai Doss · Mar 6, 2026 · Citations: 0
Pairwise Preference Long Horizon
We present RAPTOR, Representation Aware Pairwise-gated Transformer for Out-of-domain Recognition a controlled study of compact SSL backbones from the HuBERT and WavLM within a unified pairwise-gated fusion detector, evaluated across 14…
- Tutoring Large Language Models to be Domain-adaptive, Precise, and Safe
Somnath Banerjee · Feb 14, 2026 · Citations: 0
Pairwise Preference Long Horizon
The methodological trajectory moves from classical supervised adaptation for task-specific demands to decoding-time alignment for safety, finally leveraging human feedback and preference modeling to achieve sociolinguistic acuity.
- Penalizing Length: Uncovering Systematic Bias in Quality Estimation Metrics
Yilin Zhang, Wenda Xu, Zhongtao Liu, Tetsuji Nakagawa, Markus Freitag · Oct 24, 2025 · Citations: 0
Pairwise Preference Llm As Judge
Quality Estimation (QE) metrics are vital in machine translation for reference-free evaluation and increasingly serve as selection criteria in data filtering and candidate reranking.
- Semantic Alignment across Ancient Egyptian Language Stages via Normalization-Aware Multitask Learning
He Huang · Mar 25, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
We evaluate alignment quality using pairwise metrics, specifically ROC-AUC and triplet accuracy, on curated Egyptian-English and intra-Egyptian cognate datasets.
- MuRating: A High Quality Data Selecting Approach to Multilingual Large Language Model Pretraining
Zhixun Chen, Ping Guo, Wenhan Han, Yifan Zhang, Binbin Liu · Jul 2, 2025 · Citations: 0
Pairwise Preference Automatic Metrics
We introduce MuRating, a scalable framework that transfers high-quality English data-quality signals into a single rater for 17 target languages.
- Bridging the Multilingual Safety Divide: Efficient, Culturally-Aware Alignment for Global South Languages
Somnath Banerjee, Rima Hazra, Animesh Mukherjee · Feb 14, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Yet safety pipelines, benchmarks, and alignment still largely target English and a handful of high-resource languages, implicitly assuming safety and factuality ''transfer'' across languages.
- CRANE: Causal Relevance Analysis of Language-Specific Neurons in Multilingual Large Language Models
Yifan Le, Yunliang Li · Jan 8, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Prior work has identified language-related neurons mainly through activation-based heuristics, which conflate language preference with functional importance.
- Rethinking Metrics for Lexical Semantic Change Detection
Roksana Goworek, Haim Dubossarsky · Feb 17, 2026 · Citations: 0
Pairwise Preference Automatic Metrics
Lexical semantic change detection (LSCD) increasingly relies on contextualised language model embeddings, yet most approaches still quantify change using a small set of semantic change metrics, primarily Average Pairwise Distance (APD) and
- Align Once, Benefit Multilingually: Enforcing Multilingual Consistency for LLM Safety Alignment
Yuyan Bu, Xiaohao Liu, ZhaoXing Ren, Yaodong Yang, Juntao Dai · Feb 18, 2026 · Citations: 0
Pairwise Preference
The widespread deployment of large language models (LLMs) across linguistic communities necessitates reliable multilingual safety alignment.
- A Parallel Cross-Lingual Benchmark for Multimodal Idiomaticity Understanding
Dilara Torunoğlu-Selamet, Dogukan Arslan, Rodrigo Wilkens, Wei He, Doruk Eryiğit · Jan 13, 2026 · Citations: 0
Pairwise Preference
The dataset, containing 34 languages and over ten thousand items, allows comparative analyses of idiomatic patterns among language-specific realisations and preferences in order to gather insights about shared cultural aspects.
- Plausibility as Commonsense Reasoning: Humans Succeed, Large Language Models Do not
Sercan Karakaş · Apr 6, 2026 · Citations: 0
Pairwise Preference
Large language models achieve strong performance on many language tasks, yet it remains unclear whether they integrate world knowledge with syntactic structure in a human-like, structure-sensitive way during ambiguity resolution.
- Cross-Preference Learning for Sentence-Level and Context-Aware Machine Translation
Ying Li, Xinglin Lyu, Junhui Li, Jinlong Yang, Hengchao Shang · Mar 26, 2026 · Citations: 0
Pairwise Preference
In this paper, we propose Cross-Preference Learning (CPL), a preference-based training framework that explicitly captures the complementary benefits of sentence-level and context-aware MT.
- Multilingual KokoroChat: A Multi-LLM Ensemble Translation Method for Creating a Multilingual Counseling Dialogue Dataset
Ryoma Suzuki, Zhiyang Qi, Michimasa Inaba · Mar 24, 2026 · Citations: 0
Pairwise Preference
The quality of ``Multilingual KokoroChat'' was rigorously validated through human preference studies.
- Gender Bias in MT for a Genderless Language: New Benchmarks for Basque
Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez · Mar 9, 2026 · Citations: 0
Pairwise Preference
WinoMTeus adapts the WinoMT benchmark to examine how gender-neutral Basque occupations are translated into gendered languages such as Spanish and French.
- EstLLM: Enhancing Estonian Capabilities in Multilingual LLMs via Continued Pretraining and Post-Training
Aleksei Dorkin, Taido Purason, Emil Kalbaliyev, Hele-Andra Kuulmets, Marii Ojastu · Mar 2, 2026 · Citations: 0
Pairwise Preference
We subsequently apply supervised fine-tuning, preference optimization, and chat vector merging to introduce robust instruction-following behavior.
- ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection
Changjiang Gao, Zixian Huang, Kaichen Yang, Jiajun Chen, Jixing Li · Feb 25, 2026 · Citations: 0
Pairwise Preference
Analysis shows that, by enabling on-policy thinking language selection as an action during RL, ExpLang effectively extends the RL exploration space with diversified language preference and improves the RL exploitation outcome with leveraged…
- Enhancing Multilingual RAG Systems with Debiased Language Preference-Guided Query Fusion
Jeonghyun Park, Byeongjeong Kim, Seojin Hwang, Hwanhee Lee · Jan 6, 2026 · Citations: 0
Pairwise Preference
To address these biases, we propose DeLP (Debiased Language Preference), a calibrated metric designed to explicitly factor out these structural confounds.
- Fluent Alignment with Disfluent Judges: Post-training for Lower-resource Languages
David Samuel, Lilja Øvrelid, Erik Velldal, Andrey Kutuzov · Dec 9, 2025 · Citations: 0
Pairwise Preference
Preference optimization is now a well-researched topic, but previous work has mostly addressed models for English and Chinese.
- Instructing Large Language Models for Low-Resource Languages: A Systematic Study for Basque
Oscar Sainz, Naiara Perez, Julen Etxaniz, Joseba Fernandez de Landa, Itziar Aldabe · Jun 9, 2025 · Citations: 0
Pairwise Preference
We present a comprehensive set of experiments for Basque that systematically study different combinations of these components evaluated on benchmarks and human preferences from 1,680 participants.