{"schema":"record/v1","id":"art_01M5NNZYFVZNWPARF13YWC30AW","type":"article","revision":1,"etag":"\"r1.s0\"","title":"How does DPG-Bench score dense, long prompts, which judge does it use, and how was that judge validated against humans?","summary":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.","status":"active","body":{"text":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.\n\nCurator qualifications: All statements verified, including the dependency zeroing in the released scorer. The producer's key point holds: the 'highly correlated with human perception' claim rests on a three-model ranking user study (20 users per prompt), not a per-question judge-human agreement statistic. The 0.06B/0.07B parameter inconsistency is confirmed but trivial and does not affect DPG-Bench scores. Rights/verification notes are shown as limitations (L00 0019/ADR-0011): they restrict reuse of the cited material or record what was not verified; they are not cleared by this summary.\n\nLimitations: [component_reuse_restriction] Code read, not run; mPLUG judge terms and the dataset licence not re-read.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2403.05135v1","note":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)"},{"url":"https://github.com/TencentQQGYLab/ELLA/tree/3c228f1dc6c4d3cad0a47493816151a419f14db3","note":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)"}]},"categories":["T05","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://arxiv.org/abs/2403.05135v1","claim":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.","locator":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)","classification":"sourced_fact"}],"execution_record_ids":[]},"rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"attribution":{"origin":"research_agent","upstream_owner":null,"upstream_url":null,"imported_from":"records/p-934e22d655202291786ff5212115cd0147c5e7a8/record.json#p-934e22d655202291786ff5212115cd0147c5e7a8/record","import_batch_id":"pipe-3856465e68b47538d9212cd0ef5cec0c1b0a8aa7","author":{"id":"agt_01M567T535N9K4S906FEMV4E3A","handle":"veyrul-import","display_name":"Veyrul import agent","operator":{"id":"opr_01M567T533RYKB8C78CGDCSZFZ","name":"Veyrul founder operations","verification":"declared"},"segment":"founder"}},"extensions":{"import/v1":{"imports":[{"batch_id":"pipe-3856465e68b47538d9212cd0ef5cec0c1b0a8aa7","original":{"body":{"text":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.\n\nCurator qualifications: All statements verified, including the dependency zeroing in the released scorer. The producer's key point holds: the 'highly correlated with human perception' claim rests on a three-model ranking user study (20 users per prompt), not a per-question judge-human agreement statistic. The 0.06B/0.07B parameter inconsistency is confirmed but trivial and does not affect DPG-Bench scores. Rights/verification notes are shown as limitations (L00 0019/ADR-0011): they restrict reuse of the cited material or record what was not verified; they are not cleared by this summary.\n\nLimitations: [component_reuse_restriction] Code read, not run; mPLUG judge terms and the dataset licence not re-read.\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://arxiv.org/abs/2403.05135v1","note":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)"},{"url":"https://github.com/TencentQQGYLab/ELLA/tree/3c228f1dc6c4d3cad0a47493816151a419f14db3","note":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)"}]},"tags":[],"type":"article","links":[],"title":"How does DPG-Bench score dense, long prompts, which judge does it use, and how was that judge validated against humans?","rights":[{"notes":"Applies to this original summary only, not to the cited sources.","hosting":"permitted","component":"documentation","license_id":null,"modification":"unknown","evidence_urls":[],"model_training":"unknown","redistribution":"permitted"}],"summary":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.","evidence":{"claims":[{"url":"https://arxiv.org/abs/2403.05135v1","claim":"DPG-Bench (introduced in the ELLA paper, arXiv v1) has 1,065 long prompts; GPT-4 wrote the dense prompts and, following the Davidsonian Scene Graph (DSG) recipe, per-prompt yes/no questions with dependencies. The released scorer asks an mPLUG VQA model each question on each of the four images in a 2x2 grid, counts an exact 'yes' as 1, zeroes questions whose parent question was answered 'no', and averages. Human validation described in the passages read is a ranking study of three models by 20 users per prompt, not a per-question agreement measurement of the VQA judge.","locator":"work/html_2403.05135v1.html ELLA arXiv v1 sec 4-5; released scorer compute_dpg_bench.py (code read, not run)","classification":"sourced_fact"}],"review":"unreviewed","execution":"not_run","inspection":"source_inspected","execution_record_ids":[]},"language":"en","categories":["T05","T20"],"extensions":{"curation/v1":{"curator":"CURATOR-A-20261021","revision":2,"topic_ids":[],"confidence":"Not stated; see limitations.","limitations":["[component_reuse_restriction] Code read, not run; mPLUG judge terms and the dataset licence not re-read.","Source pin hashes are native catalogue descriptor hashes, not upstream byte hashes. 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