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51.5 kB
| { | |
| "title": "CMDB-1500", | |
| "question_count": 1500, | |
| "source_or_subtask_count": 79, | |
| "source_definition": "79 source and subtask identifiers; multiple subtasks may share an upstream dataset.", | |
| "sources": [ | |
| { | |
| "source": "AI2D", | |
| "selected_questions": 30, | |
| "sector": "visual", | |
| "original_splits": { | |
| "test": 30 | |
| }, | |
| "kinds": { | |
| "choice": 30 | |
| }, | |
| "upstream_url": "https://huggingface.co/datasets/lmms-lab/ai2d", | |
| "description": "Science diagram multiple-choice questions." | |
| }, | |
| { | |
| "source": "ALFRED-high-level-action", | |
| "selected_questions": 19, | |
| "sector": "embodied_actions", | |
| "original_splits": { | |
| "dev": 19 | |
| }, | |
| "kinds": { | |
| "choice": 19 | |
| }, | |
| "upstream_url": "https://github.com/askforalfred/alfred", | |
| "description": "Select the demonstrated next high-level action from a task and previous actions." | |
| }, | |
| { | |
| "source": "ALFWorld-expert-action-full", | |
| "selected_questions": 18, | |
| "sector": "embodied_actions", | |
| "original_splits": { | |
| "dev": 18 | |
| }, | |
| "kinds": { | |
| "choice": 18 | |
| }, | |
| "upstream_url": "https://github.com/alfworld/alfworld", | |
| "description": "Select the demonstrated action from a task and textual observation." | |
| }, | |
| { | |
| "source": "Aegis-annotation", | |
| "selected_questions": 44, | |
| "sector": "safety", | |
| "original_splits": { | |
| "test": 44 | |
| }, | |
| "kinds": { | |
| "choice": 44 | |
| }, | |
| "upstream_url": "https://huggingface.co/datasets/nvidia/Aegis-AI-Content-Safety-Dataset-1.0", | |
| "description": "Content safety classification using human annotations." | |
| }, | |
| { | |
| "source": "BFCL-v3", | |
| "selected_questions": 25, | |
| "sector": "tools", | |
| "original_splits": { | |
| "test": 10, | |
| "dev": 15 | |
| }, | |
| "kinds": { | |
| "choice": 25 | |
| }, | |
| "upstream_url": "https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard", | |
| "description": "Judge whether a tool call is needed." | |
| }, | |
| { | |
| "source": "ChineseHP", | |
| "selected_questions": 50, | |
| "sector": "chinese_speech_candidate_judgment", | |
| "original_splits": { | |
| "test": 50 | |
| }, | |
| "kinds": { | |
| "choice": 50 | |
| }, | |
| "upstream_url": "https://github.com/tzyll/ChineseHP", | |
| "description": "Select among AISHELL-4 N-best text hypotheses using reference-based character edit distance." | |
| }, | |
| { | |
| "source": "DecisionBench/AGT-1", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which tool to call", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "bfcl-v3-live", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#bfcl-v3-live", | |
| "dataset_name": "BFCL v3 Live (Berkeley Function-Calling Leaderboard)" | |
| } | |
| ], | |
| "description": "Select a tool for a user request" | |
| }, | |
| { | |
| "source": "DecisionBench/AGT-2", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Did the injection succeed?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "agentdojo", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#agentdojo", | |
| "dataset_name": "AgentDojo recorded runs" | |
| } | |
| ], | |
| "description": "Judge whether a prompt injection hijacked an agent" | |
| }, | |
| { | |
| "source": "DecisionBench/AGT-3", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Did the agent complete the task?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "tau-bench", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#tau-bench", | |
| "dataset_name": "τ-bench historical trajectories" | |
| } | |
| ], | |
| "description": "Judge whether an agent completed the user task" | |
| }, | |
| { | |
| "source": "DecisionBench/AGT-4", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Is the answer backed by sources?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "hagrid", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#hagrid", | |
| "dataset_name": "HAGRID" | |
| } | |
| ], | |
| "description": "Verify whether cited evidence supports an answer" | |
| }, | |
| { | |
| "source": "DecisionBench/AGT-5", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which reply is better?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "mt-bench-human", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#mt-bench-human", | |
| "dataset_name": "MT-Bench human judgments" | |
| } | |
| ], | |
| "description": "Compare the quality of two responses" | |
| }, | |
| { | |
| "source": "DecisionBench/COM-1", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Does this product match the query?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "amazon-esci", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#amazon-esci", | |
| "dataset_name": "Amazon Shopping Queries Dataset (ESCI)" | |
| } | |
| ], | |
| "description": "Assess product relevance to a shopping query" | |
| }, | |
| { | |
| "source": "DecisionBench/COM-2", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "What type of product is this?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "amazon-berkeley-objects", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#amazon-berkeley-objects", | |
| "dataset_name": "Amazon Berkeley Objects (ABO)" | |
| } | |
| ], | |
| "description": "Identify a product type" | |
| }, | |
| { | |
| "source": "DecisionBench/COM-3", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which industry is this company in?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "edgar-corpus-10k-business", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#edgar-corpus-10k-business", | |
| "dataset_name": "EDGAR-CORPUS (10-K Item 1) with SEC EDGAR SIC codes" | |
| } | |
| ], | |
| "description": "Identify a company industry" | |
| }, | |
| { | |
| "source": "DecisionBench/DAT-1", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which SQL answers the question?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "spider", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#spider", | |
| "dataset_name": "Spider (dev set)" | |
| } | |
| ], | |
| "description": "Select the SQL query that answers a question" | |
| }, | |
| { | |
| "source": "DecisionBench/DAT-2", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which cell answers the question?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "wikitablequestions", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#wikitablequestions", | |
| "dataset_name": "WikiTableQuestions (test set)" | |
| } | |
| ], | |
| "description": "Locate the table cell that answers a question" | |
| }, | |
| { | |
| "source": "DecisionBench/DAT-4", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "What does this column hold?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "congress-legislators", | |
| "selected_questions": 2, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#congress-legislators", | |
| "dataset_name": "congress-legislators (legislators-current.csv)" | |
| }, | |
| { | |
| "dataset_id": "federal-register", | |
| "selected_questions": 3, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#federal-register", | |
| "dataset_name": "Federal Register documents API" | |
| }, | |
| { | |
| "dataset_id": "fiscal-data", | |
| "selected_questions": 1, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#fiscal-data", | |
| "dataset_name": "U.S. Treasury Fiscal Data" | |
| }, | |
| { | |
| "dataset_id": "fivethirtyeight", | |
| "selected_questions": 4, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#fivethirtyeight", | |
| "dataset_name": "FiveThirtyEight data repository" | |
| } | |
| ], | |
| "description": "Identify the meaning of a data column" | |
| }, | |
| { | |
| "source": "DecisionBench/DOC-2", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Decision, action item, or neither?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "ami", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#ami", | |
| "dataset_name": "AMI Meeting Corpus" | |
| } | |
| ], | |
| "description": "Classify meeting text as a decision, action item, or neither" | |
| }, | |
| { | |
| "source": "DecisionBench/DOC-3", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which summary is this meeting's?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "ami", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#ami", | |
| "dataset_name": "AMI Meeting Corpus" | |
| } | |
| ], | |
| "description": "Select the summary corresponding to a meeting" | |
| }, | |
| { | |
| "source": "DecisionBench/ENG-1", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which file must change?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "swe-bench-verified", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#swe-bench-verified", | |
| "dataset_name": "SWE-bench Verified" | |
| } | |
| ], | |
| "description": "Locate the file that needs to change to resolve an issue" | |
| }, | |
| { | |
| "source": "DecisionBench/ENG-2", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "What kind of change is this?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "commitpackft", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#commitpackft", | |
| "dataset_name": "CommitPackFT" | |
| } | |
| ], | |
| "description": "Classify the type of a code change" | |
| }, | |
| { | |
| "source": "DecisionBench/ENG-3", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which weakness class is this?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "nvd", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#nvd", | |
| "dataset_name": "NVD (National Vulnerability Database)" | |
| } | |
| ], | |
| "description": "Identify a vulnerability weakness class" | |
| }, | |
| { | |
| "source": "DecisionBench/ENG-4", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Live secret or placeholder?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "creddata", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#creddata", | |
| "dataset_name": "Samsung CredData" | |
| } | |
| ], | |
| "description": "Distinguish a real secret from a placeholder" | |
| }, | |
| { | |
| "source": "DecisionBench/ENG-5", | |
| "selected_questions": 10, | |
| "sector": "domain_decisions", | |
| "original_splits": { | |
| "test": 10 | |
| }, | |
| "kinds": { | |
| "choice": 10 | |
| }, | |
| "immediate_source_url": "https://github.com/atlanai/decision-bench", | |
| "immediate_source_revision": "6fed2cd4c3608b070e649180796ccaef3d020a23", | |
| "immediate_corpus": "bench-v4", | |
| "task_name": "Which message describes this diff?", | |
| "upstream_sources": [ | |
| { | |
| "dataset_id": "commitpackft", | |
| "selected_questions": 10, | |
| "source_catalog_url": "https://github.com/atlanai/decision-bench/blob/6fed2cd4c3608b070e649180796ccaef3d020a23/data/SOURCES.md#commitpackft", | |
| "dataset_name": "CommitPackFT" | |
| } | |
| ], | |
| "description": "Select a commit message for a code diff" | |
| }, | |
| { | |
| "source": "DecisionBench/FIN-1", | |
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| "dataset_name": "SEC EDGAR 8-K filings" | |
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| "description": "Identify the event reported in an 8-K filing" | |
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| { | |
| "source": "DecisionBench/FIN-4", | |
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| "dataset_id": "finer-139", | |
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| "dataset_name": "FiNER-139" | |
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| "description": "Identify the financial concept represented by a number" | |
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| { | |
| "source": "DecisionBench/LEG-1", | |
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| "dataset_id": "contractnli", | |
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| "dataset_name": "ContractNLI" | |
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| ], | |
| "description": "Determine whether an NDA supports a statement" | |
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| { | |
| "source": "DecisionBench/LEG-2", | |
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| "dataset_id": "cuad", | |
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| "description": "Identify a contract clause type" | |
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| "dataset_id": "lexglue-unfair-tos", | |
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| "dataset_name": "UNFAIR-ToS (LexGLUE)" | |
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| "description": "Identify an unfair terms-of-service clause and its category" | |
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| "source": "DecisionBench/LEG-4", | |
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| "dataset_id": "cuad", | |
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| "description": "Determine whether a contract includes a specified clause" | |
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| "source": "DecisionBench/PRD-1", | |
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| "dataset_id": "upworthy-archive", | |
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| "dataset_name": "Upworthy Research Archive (exploratory packages)" | |
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| { | |
| "source": "DecisionBench/PRD-2", | |
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| "task_name": "Attack on the assistant", | |
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| "dataset_id": "deepset-prompt-injections", | |
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| "dataset_name": "TrustAIRLab/in-the-wild-jailbreak-prompts" | |
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| "description": "Distinguish prompt injection, jailbreak, and benign requests" | |
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| { | |
| "source": "DecisionBench/SAF-2", | |
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| "dataset_name": "google/civil_comments" | |
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| "description": "Identify toxic comments" | |
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| { | |
| "source": "DecisionBench/SUP-1", | |
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| "description": "Route a consumer complaint to the responsible product team" | |
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| { | |
| "source": "DecisionBench/SUP-2", | |
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