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How Many Demonstrations Do You Need for In-context Learning?

, , , and . EMNLP (Findings), page 11149-11159. Association for Computational Linguistics, (2023)

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OPTune: Efficient Online Preference Tuning., , , , , , , , and . CoRR, (2024)Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection., , , , , , , , and . NAACL-HLT, page 6065-6086. Association for Computational Linguistics, (2024)Spectrum AUC Difference (SAUCD): Human-aligned 3D Shape Evaluation., , , , , , and . CoRR, (2024)PTP: Boosting Stability and Performance of Prompt Tuning with Perturbation-Based Regularizer., , , and . EMNLP, page 13512-13525. Association for Computational Linguistics, (2023)Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning., , , , , , and . CoRR, (2024)From Quantity to Quality: Boosting LLM Performance with Self-Guided Data Selection for Instruction Tuning., , , , , , , , and . NAACL-HLT, page 7602-7635. Association for Computational Linguistics, (2024)HallusionBench: You See What You Think? Or You Think What You See? An Image-Context Reasoning Benchmark Challenging for GPT-4V(ision), LLaVA-1.5, and Other Multi-modality Models., , , , , , and . CoRR, (2023)GPT-4 Vision on Medical Image Classification - A Case Study on COVID-19 Dataset., , , , , , , , and . CoRR, (2023)Unbiased Watermark for Large Language Models., , , , , and . CoRR, (2023)Graph Edit Distance Reward: Learning to Edit Scene Graph., , , and . ECCV (19), volume 12364 of Lecture Notes in Computer Science, page 539-554. Springer, (2020)