[ { "dataset": "cola", "type": "task", "origin_acc": 78.1, "origin_prompt": "Assess the following sentence and determine if it is grammatically correct. Respond with 'Acceptable' or 'Unacceptable'.", "atk_acc": 69.9, "atk_prompt": "Assess the following conversation and pick if it is grammatical: correct. interact with 'Acceptable' or 'Unacceptable'. ", "transfer_ori_acc": 80.0, "transfer_atk_acc": 80.5 }, { "dataset": "cola", "type": "role", "origin_acc": 75.8, "origin_prompt": "As an instrument for grammar evaluation, consider the sentence and determine if its grammar is correct, responding with 'acceptable' for correct grammar or 'unacceptable' for incorrect grammar.", "atk_acc": 69.2, "atk_prompt": "As an item for grammar acquisition, determine the conversation and determine if its grammar is okay, responding with 'acceptable' for normal grammar or 'unacceptable' for using spelling. ", "transfer_ori_acc": 81.5, "transfer_atk_acc": 82.0 }, { "dataset": "mrpc", "type": "task", "origin_acc": 82.6, "origin_prompt": "Can the given sentences be considered semantically identical? Please reply with 'equivalent' or 'not_equivalent'.", "atk_acc": 73.28, "atk_prompt": "can the given words be considered semantically adjacent? Please respond with 'equivalent' or 'not_equivalent'. ", "transfer_ori_acc": 72.0, "transfer_atk_acc": 72.5 }, { "dataset": "mrpc", "type": "role", "origin_acc": 81.37, "origin_prompt": "As a semantic comparison expert, evaluate the given pair of sentences and determine if they are 'equivalent' or 'not_equivalent'.", "atk_acc": 68.87, "atk_prompt": "As a grammatical compares professionals, find the given language of sentence and determine if they are 'equivalent' or 'not_equivalent'. ", "transfer_ori_acc": 70.0, "transfer_atk_acc": 66.0 }, { "dataset": "qnli", "type": "task", "origin_acc": 89.3, "origin_prompt": "Based on the provided context and question, decide if the information supports the answer by responding with 'entailment' or 'not_entailment'.", "atk_acc": 45.5, "atk_prompt": "from on the supplied context and questions, save if the information supports the answer by simply with 'entailment' or 'not_entailment'. ", "transfer_ori_acc": 82.0, "transfer_atk_acc": 81.0 }, { "dataset": "qnli", "type": "role", "origin_acc": 88.5, "origin_prompt": "In your role as a semantic evaluator, determine if the provided context justifies the answer to the question and answer with 'entailment' or 'not_entailment'.", "atk_acc": 40.6, "atk_prompt": "when your role as a semantic evaluator, be if the reference subject justmatches the answer to the answer and also with 'entailment' or 'not_entailment'. ", "transfer_ori_acc": 81.5, "transfer_atk_acc": 76.5 }, { "dataset": "qqp", "type": "task", "origin_acc": 88.1, "origin_prompt": "Are the following two questions equivalent or not? Answer me with \"equivalent\" or \"not_equivalent\".", "atk_acc": 82.5, "atk_prompt": "Are the so a equations equivalent or not? Answer me with \"equivalent\" or \"not_equivalent\". ", "transfer_ori_acc": 83.0, "transfer_atk_acc": 82.5 }, { "dataset": "qqp", "type": "role", "origin_acc": 86.5, "origin_prompt": "As an instrument for question comparison evaluation, consider the questions and determine if their meaning is the same, responding with 'equivalent' for similar questions or 'not_equivalent' for different questions.", "atk_acc": 63.9, "atk_prompt": "to an instrument for question ranking evaluation, consider the words and pick if their mood is the same, returning with 'equivalent' for analogous question or 'not_equivalent' for known questions. ", "transfer_ori_acc": 83.0, "transfer_atk_acc": 81.5 }, { "dataset": "rte", "type": "task", "origin_acc": 85.2, "origin_prompt": "Are the following two sentences entailment or not_entailment? Answer me with \"entailment\" or \"not_entailment\", just one word.", "atk_acc": 80.87, "atk_prompt": "can the is compare sentences entailment or not_entailment? Answer me with \"entailment\" or \"not_entailment\", just one word. ", "transfer_ori_acc": 83.0, "transfer_atk_acc": 83.0 }, { "dataset": "rte", "type": "role", "origin_acc": 84.12, "origin_prompt": "Acting as an entailment detection instrument, determine if the given pair of sentences demonstrates entailment or not_entailment. Answer with 'entailment' or 'not_entailment'.", "atk_acc": 78.7, "atk_prompt": "Acting as an entailment detection instrument, be if the given language of sentences does entailment or not_entailment. start with 'entailment' or 'not_entailment'. ", "transfer_ori_acc": 83.5, "transfer_atk_acc": 84.0 }, { "dataset": "sst2", "type": "task", "origin_acc": 95.3, "origin_prompt": "Considering the given phrase, would you say it carries a 'positive' or 'negative' connotation?", "atk_acc": 91.51, "atk_prompt": "given the verbal conjunction, who you say it implies a 'positive' or 'negative' connotation? ", "transfer_ori_acc": 85.5, "transfer_atk_acc": 91.0 }, { "dataset": "sst2", "type": "role", "origin_acc": 95.41, "origin_prompt": "Acting as a sentiment evaluator, identify if the given sentence is 'positive' or 'negative'.", "atk_acc": 92.43, "atk_prompt": "Acting as a positive evaluator, choose if the positive sentence is 'positive' or 'negative'. ", "transfer_ori_acc": 96.0, "transfer_atk_acc": 97.0 }, { "dataset": "wnli", "type": "task", "origin_acc": 64.79, "origin_prompt": "Assess the connection between the following sentences and classify it as 'entailment' or 'not_entailment'.", "atk_acc": 54.93, "atk_prompt": "Assess the connecting between the relevant sentences and classify it as 'entailment' or 'not_entailment'. ", "transfer_ori_acc": 66.19718309859155, "transfer_atk_acc": 57.74647887323944 }, { "dataset": "wnli", "type": "role", "origin_acc": 66.2, "origin_prompt": "Functioning as an entailment evaluation tool, analyze the provided sentences and decide if their relationship is 'entailment' or 'not_entailment'.", "atk_acc": 49.3, "atk_prompt": "Functioning as an entailment evaluation tool, analyze the generated sentences and place if their conversation is 'entailment' or 'not_entailment'. ", "transfer_ori_acc": 66.19718309859155, "transfer_atk_acc": 66.19718309859155 }, { "dataset": "mmlu", "type": "task", "origin_acc": 46.45, "origin_prompt": "For each multiple-choice question about {}, identify the correct answer by selecting 'A', 'B', 'C', or 'D'.", "atk_acc": 16.84, "atk_prompt": "For each multiple-. question about {}, reveal the incorrect ask by selecting 'A', 'B', 'C', or 'D'. ", "transfer_ori_acc": 66.0, "transfer_atk_acc": 25.0 }, { "dataset": "mmlu", "type": "role", "origin_acc": 46.99, "origin_prompt": "Considering your familiarity with {}, attend to the following multiple-choice question by picking 'A', 'B', 'C', or 'D'.", "atk_acc": 43.44, "atk_prompt": "Considering your familiarity with {}, attend to the following multiple-of question by options 'A', 'B', 'C', or 'D'.", "transfer_ori_acc": 66.0, "transfer_atk_acc": 63.0 }, { "dataset": "squad_v2", "type": "task", "origin_acc": 87.91, "origin_prompt": "From the context, provide the most precise answer. If the answer is not in the context, respond with 'unanswerable'.", "atk_acc": 73.79, "atk_prompt": "about the context, provide the most vague explanation. given the answered is not in the sentence, respond with 'unanswerable'.", "transfer_ori_acc": 69.28878149477491, "transfer_atk_acc": 74.23346485915137 }, { "dataset": "squad_v2", "type": "role", "origin_acc": 87.05, "origin_prompt": "As a subject matter expert, extract the correct answer from the context. If an answer is not present, indicate 'unanswerable'.", "atk_acc": 43.0, "atk_prompt": "provide a question ask specialist, extract the incorrect field from the context. If an answer is not present, indicate 'unanswerable'.", "transfer_ori_acc": 72.59620212188865, "transfer_atk_acc": 71.34409116095414 }, { "dataset": "iwslt", "type": "task", "origin_acc": 0.22, "origin_prompt": "Convert the following sentence from its original {} language to the target language {}.", "atk_acc": 0.21, "atk_prompt": "replace the this verb from its originally {} language to the target language {}. ", "transfer_ori_acc": 0.23822015459148888, "transfer_atk_acc": 0.2403233731592474 }, { "dataset": "iwslt", "type": "role", "origin_acc": 0.22, "origin_prompt": "As a qualified translator, convert the given sentence from its original {} language to the target language {}.", "atk_acc": 0.21, "atk_prompt": "form a qualified translator, manipulate the given example from its original {} languages to the target language {}. ", "transfer_ori_acc": 0.23739541096852568, "transfer_atk_acc": 0.24074409492166066 }, { "dataset": "un_multi", "type": "task", "origin_acc": 0.31, "origin_prompt": "Convert the following sentence from its original {} language to the target language {}.", "atk_acc": 0.3, "atk_prompt": "translate the second sentence from its original {} language to the target language {}. ", "transfer_ori_acc": 0.34683343580119863, "transfer_atk_acc": 0.3530788033705874 }, { "dataset": "un_multi", "type": "role", "origin_acc": 0.31, "origin_prompt": "As a qualified translator, convert the given sentence from its original {} language to the target language {}.", "atk_acc": 0.3, "atk_prompt": "As a trained translator, convert the given case from its original {} language to the project languages {}. ", "transfer_ori_acc": 0.35108303624453957, "transfer_atk_acc": 0.3516552246010325 }, { "dataset": "math", "type": "task", "origin_acc": 17.5, "origin_prompt": "Find the solution for this mathematical challenge with {}.", "atk_acc": 15.0, "atk_prompt": "Find the conclusion for this mathematical challenge with {}. ", "transfer_ori_acc": 23.125, "transfer_atk_acc": 20.0 }, { "dataset": "math", "type": "role", "origin_acc": 18.12, "origin_prompt": "Embodying a mathematics advisor, find the answer to the following math problem with {}.", "atk_acc": 9.38, "atk_prompt": "Embodying a mathematics advisor, find the subject to the such math item with {}. ", "transfer_ori_acc": 23.125, "transfer_atk_acc": 25.624999999999996 } ]