Papers with sentence completion
SharPT: Shared Latent Space Prompt Tuning (2023.findings-eacl)
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| Challenge: | Prompt tuning is an efficient method for adapting large language models, but it is difficult and expensive to identify the source task that provides optimal prompts. |
| Approach: | They propose to learn a shared latent space which captures a set of basis skills from a mixture of source tasks and then transfer them to target tasks. |
| Outcome: | The proposed method outperforms previous methods on NLI, sentence completion, QA, conference resolution, word sense disambiguation and on various model scales. |
Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering (2022.emnlp-main)
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| Challenge: | Existing approaches to multi-choice question answering are based on binary classifications instead of scoring each answer as a single class. |
| Approach: | They propose a simple refactoring of multi-choice question answering tasks as a series of binary classifications and propose re-framing to make them more efficient. |
| Outcome: | The proposed approach is significantly more effective across different tasks and models. |
BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs (2024.emnlp-main)
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| Challenge: | Existing evaluation approaches rely on fixed-form outputs and cannot adapt to flexible open-text generation scenarios. |
| Approach: | They propose a plug-and-play tool to detect social bias in open-text LLMs. |
| Outcome: | Extensive experiments show that BiasAlert outperforms state-of-the-art methods in detecting bias in open-text generation scenarios. |
Incomplete Prompt Jailbreaks in Large Language Models (2026.findings-acl)
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| Challenge: | Large language models (LLMs) are increasingly released as open-weight models with safeguards against harmful requests. |
| Approach: | They formalize incomplete prompt jailbreaks as incomplete prompts elicit harmful continuations . they identify two functional neurons that delay refusal until sentence termination . |
| Outcome: | The proposed model fails to generalize across content domains and attractor types . the proposed model can be used to perform more precise and robust IPJ defenses . |