Papers with low-cost adaptation
Rephrasing Invokes Better Generations for Large Language Models (2024.naacl-srw)
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| Challenge: | Existing methods for prompt tuning and input pre-processing are under-studied . e.g., ReLLM replaces low-frequency words with their high-frequency counterparts . |
| Approach: | They propose a method that automatically paraphrases input content for better output generation. |
| Outcome: | The proposed method is user-friendly and requires no additional training. |
CLaS-Bench: A Cross-Lingual Alignment and Steering Benchmark (2026.findings-acl)
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Daniil Gurgurov, Yusser Al Ghussin, Tanja Baeumel, Cheng-Ting Chou, Patrick Schramowski, Marius Mosbach, Josef Van Genabith, Simon Ostermann
| Challenge: | Understanding and controlling behavior of large language models (LLMs) is an important topic in multilingual NLP. |
| Approach: | They propose a lightweight parallel-question benchmark for evaluating language-forcing behavior in large language models across 32 languages. |
| Outcome: | The proposed benchmark measures language steering in 32 languages across 32 languages. |