Macro: Enhancing Multilingual Counterfactual Explanations through Alignment-as-Preference Optimization

arXiv:2605.11632 · cs.CL, cs.AI · Submitted 2026-05-12 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-05-12

Updated: 2026-08-26

Comments: Camera-ready version accepted to EMNLP 2026 Findings

Code: https://github.com/cisnlp/GlotLID

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 34× in this paper · explained in 1 episode
• Ablation — 20× in this paper · explained in 1 episode
• Cross-lingual Edit Similarity — 9× in this paper
• Ablation study — 7× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Direct Preference Optimization — 6× in this paper
• Benchmark — 4× in this paper · explained in 2 episodes
• Explainability — 4× in this paper · explained in 3 episodes
• Perplexity — 4× in this paper · explained in 3 episodes
• Semantic Similarity — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Generalizability — 3× in this paper · explained in 6 episodes
• Low-Resource Languages — 3× in this paper · explained in 4 episodes
• Soft Label Flipping Rate — 3× in this paper
• Textual Similarity — 3× in this paper
• Ablation Studies — 2× in this paper · explained in 1 episode
• Accuracy — 2× in this paper · explained in 1 episode
• Adam — 2× in this paper · explained in 2 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Direct Preference Optimization (DPO) — 2× in this paper · explained in 9 episodes
• Hard Label Flipping Rate — 2× in this paper
• Loss Function — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Reward Function — 2× in this paper · explained in 2 episodes
• Bradley-Terry model — 1× in this paper · explained in 2 episodes
• Chain-of-Thought Prompting — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Evaluation Dimensions — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• RAG — 1× in this paper · explained in 3 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• From Fragments to Facts: A Curriculum-Driven DPO Approach for Generating Hindi News Veracity Explanations
• DRIV-EX: Counterfactual Explanations for Driving LLMs
• Gemma 3 Technical Report
• GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
• Self-rationalization improves LLM as a fine-grained judge
• Anchored Alignment for Self-Explanations Enhancement
• Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation
• iFlip: Iterative Feedback-driven Counterfactual Example Refinement
• Qwen3 Technical Report

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