Papers with reverse alignment

2 papers
Alirector: Alignment-Enhanced Chinese Grammatical Error Corrector (2024.findings-acl)

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Challenge: Existing methods to address overcorrection in Chinese grammatical error correction (CGEC) are difficult to adapt to decoder-only large language models (LLMs).
Approach: They propose an alignment-enhanced corrector for the overcorrection problem that applies to both Seq2Seq models and decoder-only large language models (LLMs).
Outcome: The proposed corrector alleviates the overcorrection problem in Chinese grammatical error correction (CGEC) using generative models and decoder-only large language models.
On the Vulnerability of Safety Alignment in Open-Access LLMs (2024.findings-acl)

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Challenge: Large language models (LLMs) are susceptible to malicious exploitation, but are often rejected and limited harmfulness is limited.
Approach: They propose two types of reverse alignment techniques: reverse supervised fine-tuning (RSFT) and reverse preference optimization (RPO).
Outcome: The proposed methods can significantly enhance the success rate and harmfulness of jailbreak attacks, but they face high rejection rates and limited harmfulness.

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