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20242026
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cs.CL2026

Gender Bias in MT for a Genderless Language: New Benchmarks for Basque

Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez

Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…

cs.CL2025

Retriv at BLP-2025 Task 2: Test-Driven Feedback-Guided Framework for Bangla-to-Python Code Generation

K M Nafi Asib, Sourav Saha, Mohammed Moshiul Hoque

Large Language Models (LLMs) have advanced the automated generation of code from natural language prompts. However, low-resource languages (LRLs) like Bangla remain underrepresente…

cs.CL2025

SEA-LION: Southeast Asian Languages in One Network

Raymond Ng, Thanh Ngan Nguyen, Yuli Huang +28

Recently, Large Language Models (LLMs) have dominated much of the artificial intelligence scene with their ability to process and generate natural languages. However, the majority…

cs.CL2025

RTTC: Reward-Guided Collaborative Test-Time Compute

J. Pablo Muñoz, Jinjie Yuan

Test-Time Compute (TTC) has emerged as a powerful paradigm for enhancing the performance of Large Language Models (LLMs) at inference, leveraging strategies such as Test-Time Train…

cs.CL2025

From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation

Seokhee Hong, Sunkyoung Kim, Guijin Son +3

The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…