arXiv AI

Estimating Grammatical Gender Directions in Contextual Embeddings under Controlled and Natural Contexts

arXiv:2606. 30152v1 Announce Type: cross Abstract: Contextual language models conflate grammatical gender and social semantic bias in gendered languages such as Spanish.

arXiv AI

Aug 11

Mitigating Gender Bias in English to Romanian Machine Translation

arXiv:2608. 08606v1 Announce Type: cross Abstract: Machine translation (MT) systems often fail to correctly translate gender, especially when converting from a gender-neutral language like English to a gendered target language such as Romanian.

By Ioana Grigore, Sergiu Nisioi

llms nlp fine-tuning benchmarks safety

arXiv AI

Jun 2

Failure of contextual invariance in large language models

arXiv:2603. 23485v2 Announce Type: replace-cross Abstract: Standard evaluation practices assume that large language model (LLM) outputs are stable when prompts are embedded in contextually equivalent discourses.

By Sagar Kumar, Ariel Flint, Luca Maria Aiello, Andrea Baronchelli

llms benchmarks safety

arXiv Machine Learning

Jul 23

Evaluating and Mitigating Gender Bias in Pre-trained Embeddings for ML-based Recruitment

arXiv:2607. 20073v1 Announce Type: new Abstract: AI-based recruitment systems that rely on machine learning models trained on historical CV data, risk perpetuating and amplifying social biases.

By Farnaz Faramarzi Lighvan, Lynn Houthuys

llms rag safety

arXiv AI

Jul 31

BioPro: Towards Difference-Aware Gender Fairness for Vision-Language Models

arXiv:2512. 00807v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) inherit significant social biases from their training data, notably in gender representation.

By Yujie Lin, Jiayao Ma, Qingguo Hu, Wenbo Li, Genji Li, Derek Wong, Jinsong Su

llms rag diffusion multimodal safety

arXiv Machine Learning

Aug 6

Learning Sexism Detection Using Multi-Agent Perspectivist Preference Optimization

arXiv:2608. 04056v1 Announce Type: cross Abstract: When people label text for sexism, they often disagree, and not because some of them are wrong: they genuinely perceive sexism differently.

By Hadi Mohammadi, Tina Shahedi, Robert A. Bagheri, Mehdi Dastani, Masoume M. Raeissi

llms agents nlp fine-tuning

arXiv AI

Aug 6

MERaLiON-GR: Speech Gender Recognition Model for English and SEA Languages

arXiv:2608. 04433v1 Announce Type: cross Abstract: We present MERaLiON-GR, a speech gender recognition system that performs binary classification (female / male) on English and Southeast Asian (SEA) languages.

By Qiongqiong Wang, Ai Ti Aw, Nancy F. Chen, Ying Lay Chiu, Yang Ding, Yingxu He, Ridong Jiang, Zhuohan Liu, Yanfeng Lu, Yi Ma, Muhammad Huzaifah, Nabilah Binte Md Johan, Nattadaporn Lertcheva, Pham Minh Duc, Sailor Hardik Bhupendra, Siti Umairah Binte Mohammad Salleh, Shuo Sun, Tarun Kumar Vangani, Jeremy H. M. Wong, Jinyang Wu, Longyin Zhang

llms fine-tuning benchmarks

arXiv AI

1d ago

DR.GAP: Mitigating Bias in Large Language Models using Gender-Aware Prompting with Decoupled Reasoning

arXiv:2502. 11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particularly gender bias, raising fairness concerns.

By Hongye Qiu, Yue Xu, Yi Wang, Meikang Qiu, Wenjie Wang

llms multimodal safety

arXiv AI

Aug 5

Unequal Verdicts: Investigating Gender Bias in LLM-Based Fake News Detection

arXiv:2608. 03627v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used for automated fact-checking, yet their susceptibility to gender bias in this context remains underexplored.

By Razieh Chalehchaleh, Reza Farahbakhsh, Noel Crespi

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arXiv AI

Jun 10

Ethical and Technical Limits of Deepfake Speech Datasets

arXiv:2606. 10911v1 Announce Type: cross Abstract: Claims about the robustness and fairness of deepfake speech detectors are only as credible as the datasets used to train and evaluate those systems.

By Vojt\v{e}ch Stan\v{e}k, Eva Trnovsk\'a, Kamil Malinka, Anton Firc

safety

arXiv AI

Aug 10

Calibrating WEAT Against Anisotropy: ZCA Whitening as a Geometric Pre-Processing Step for Embedding Association Tests

arXiv:2608. 06908v1 Announce Type: cross Abstract: We propose Zero-phase Component Analysis (ZCA) whitening as a geometric pre-processing step for the Word Embedding Association Test (WEAT).

By Seitaro Ono, Senna Ross, Jun Saiki

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arXiv AI

Jul 14

Polarization Detection: A Hybrid Approach with AfroXLMR-Social and DeBERTa for Low- and High-Resource Settings

arXiv:2607. 10312v1 Announce Type: cross Abstract: The rapid proliferation of online polarization threatens social cohesion, necessitating robust automated detection systems that operate effectively across diverse linguistic contexts.

By Muhammad Abdullahi Said

fine-tuning

arXiv AI

5d ago

It's How You Ask: Gender-Associated Linguistic Bias in LLMs

arXiv:2608. 13328v1 Announce Type: cross Abstract: Professional communication is increasingly mediated by LLMs - but do these models serve all users equally?

By Katherine Van Koevering, Anjalie Field

llms safety

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