{"total":7,"items":[{"citing_arxiv_id":"2608.16632","ref_index":29,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"DRAFE: Domain-Robust Asymmetric Fusion of Heterogeneous Detection Transformers for Cross-City Fine-Grained Traffic Object Detection","primary_cat":"cs.CV","submitted_at":"2026-08-17T14:32:03+00:00","verdict":"CONDITIONAL","verdict_confidence":"MODERATE","novelty_score":5.0,"formal_verification":"none","one_line_summary":"DRAFE, an asymmetric fusion ensemble of two LW-DETR and one RF-DETR detectors, achieved 0.4022 mAP and sixth place on AI City Challenge 2026 Track 6 via class-consistent matching and complementary recovery.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2608.11167","ref_index":92,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"MultiModal Code-Switching: Interleaving Visual Objects into Language for Explicit Object-Level Alignment","primary_cat":"cs.CV","submitted_at":"2026-08-11T17:28:52+00:00","verdict":"CONDITIONAL","verdict_confidence":"MODERATE","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Replacing an object's name in a caption with the image tokens of that object during pretraining gives explicit object-entity grounding, making MLLM alignment several times more data-efficient and boosting grounding and perception scores.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2608.03136","ref_index":20,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Frozen High-Resolution Inference for Cross-City Object Detection: An AI City Challenge 2026 Study","primary_cat":"cs.CV","submitted_at":"2026-08-04T05:03:37+00:00","verdict":"CONDITIONAL","verdict_confidence":"MODERATE","novelty_score":3.0,"formal_verification":"none","one_line_summary":"Frozen 1120x1120 inference of a 704-trained RF-DETR achieved +0.0382 AP over the 704 baseline on an aggregate-only hidden cross-city benchmark, and a fine-tuning run improved in-domain validation AP while its hidden AP did not rise.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.23739","ref_index":28,"ref_count":3,"confidence":0.88,"is_internal_anchor":false,"paper_title":"A Wavelet-Integrated Search Pipeline for Narrowband Technosignatures in FAST Observations of 33 Exoplanet Systems","primary_cat":"astro-ph.IM","submitted_at":"2026-05-22T15:13:59+00:00","verdict":"CONDITIONAL","verdict_confidence":"MODERATE","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A wavelet-guided neural pipeline recovers previously known narrowband radio events from FAST observations of 33 exoplanet systems and reduces 139,127 detections to 803 veto-ready candidates; 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