1 citations · 1 across the 7 of their papers we have counts for
5 papers · 1 filter
Do Language Models Track Entities Across State Changes?
Zilu Tang, Qiao Zhao, Gabriel Franco +4
Entity tracking (ET), the ability to keep track of states, is a fundamental skill that underlies complex reasoning. An increasing amount of work investigates how transformer langua…
Beyond Transfer Accuracy: Mechanism-Guided Controlled Adaptation for Low-Resource Languages
Khumaisa Nur'aini, Ayu Purwarianti, Alham Fikri Aji +1
Existing circuit discovery methods rely on templated tasks with clean counterfactuals, limiting their use on diverse natural text. We adapt Contextual Decomposition for Transformer…
mR3: Multilingual Rubric-Agnostic Reward Reasoning Models
David Anugraha, Shou-Yi Hung, Zilu Tang +3
Evaluation using Large Language Model (LLM) judges has been widely adopted in English and shown to be effective for automatic evaluation. However, their performance does not genera…
R3: Robust Rubric-Agnostic Reward Models
David Anugraha, Zilu Tang, Lester James V. Miranda +5
Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllability and interpretability. These models a…
Do Language Models Understand Honorific Systems in Javanese?
Mohammad Rifqi Farhansyah, Iwan Darmawan, Adryan Kusumawardhana +3
The Javanese language features a complex system of honorifics that vary according to the social status of the speaker, listener, and referent. Despite its cultural and linguistic s…