“the best-single baseline achieves an 82.5% +- 3.3% win rate, dramatically outperforming the best deliberation protocol(13.8% +- 2.6%)”

“CPJ significantly improves performance: using GPT-5-mini captions, GPT-5-Nano achieves +22.7 pp in disease classification and +19.5 points in QA score over no-caption baselines.”

“ADOPT explicitly models the dependency between each LLM step and the final task outcome, enabling precise text-gradient estimation analogous to computing analytical derivatives.”

“BEDA consistently outperforms strong baselines: on CKBG it improves success rate by at least 5.0 points across backbones and by 20.6 points with GPT-4.1-nano; on Mutual Friends it achieves an average improvement of 9.3 points; and on CaSiNo it achieves the optimal deal relative to all baselines.”

“ArtiSG significantly outperforms baselines in functional element recall and articulation estimation precision.”

“The model achieves 12% median relative error using discovered semantic features from multimodal listing data, substantially outperforming a GPT-5 baseline (38% error).”

“Tests on Arabic, Bangla, English, and Spanish datasets show that our approach consistently beats strong baselines.”

“The paper introduces a learnable feature embedding for segmentation in Gaussian primitives and a novel 'Embedding-to-Label' process.”

“The two-stage approach decomposes spatial reasoning into atomic building blocks and their composition.”

“The paper proposes a model that outperforms two established baselines, DINO-WM and V-JEPA-2-AC, in both navigation and manipulation tasks.”

“The approach achieves a 20.15% reduction in Mean Spectral Information Divergence (MSID), up to 1.09% PSNR improvement, and a 1.62% log transformed MS-SSIM gain over strong learned baselines.”

“The best configuration retains (93.0 +/- 0.2)% of reconstructed signal intensity while discarding (97.8 +/- 0.1)% of the image area, with an inference time of approximately 25 ms per frame on a consumer GPU.”

“Mirage achieves high realism and temporal consistency across diverse editing scenarios.”

“MedKGI improves dialogue efficiency by 30% on average while maintaining state-of-the-art accuracy.”

“The paper demonstrates significant performance gains on planning datasets in the Blocksworld domain through intrinsic self-critique, without external source such as a verifier.”

“LoongFlow outperforms leading baselines (e.g., OpenEvolve, ShinkaEvolve) by up to 60% in evolutionary efficiency while discovering superior solutions.”

“DreamTacVLA outperforms state-of-the-art VLA baselines, achieving up to 95% success, highlighting the importance of understanding physical contact for robust, touch-aware robotic agents.”

“SGR reduces the influence of noisy information and improves reasoning accuracy.”

“The accuracy rate, F1 score, recall rate and AUC of PFed-Signal are 0.887, 0.890, 0.913 and 0.957 respectively, which are higher than the baselines.”

“KernelEvolve reduces development time from weeks to hours and achieves substantial performance improvements over PyTorch baselines.”

“PEG-DRNet achieves an overall AP of 29.8%, an AP$_{50}$ of 84.3%, and a small-object AP of 25.3%, surpassing the RT-DETR-R18 baseline.”

“LENS outperforms strong baselines on standard NLP metrics and task-specific measures of symptom-severity accuracy.”

“The Simple Baseline for Multimodal Learning (SimBaMM) often performs comparably to, and sometimes outperforms, more complex architectures.”

“MetaCD outperforms other baselines in both accuracy and generalization.”

“FGMNB consistently outperforms five state-of-the-art embedding-based baselines on three of these networks.”

“USF-MAE outperformed the DenseNet-169 baseline on all evaluation metrics.”

“Both quantum models produced samples with lower average minimum distances to the true distribution compared to the LSTM, with the QCBM achieving the most favorable metrics.”

““By explicitly constraining the generation with a goal image, our method enforces physical plausibility and goal consistency throughout the generated trajectory.””

“Tyee demonstrates consistent practical effectiveness and generalizability, outperforming or matching baselines across all evaluated tasks (with state-of-the-art results on 12 of 13 datasets).”

“The method achieves a state-of-the-art score of 68.10% on the ICBHI 2017 dataset, outperforming existing CNN and hybrid baselines. More importantly, it reaches a sensitivity of 68.31%, a crucial improvement for reliable clinical screening.”

“CONTRA improves user throughput and reduces both THO and CHO switching costs, outperforming 3GPP-compliant and Reinforcement Learning (RL) baselines in dynamic and real-world scenarios.”

“DIOR outperforms existing training-free baselines, including CLIP.”

“The jointly trained model achieves Tumor Dice scores of 76.7% on CT and 78.3% on MRI, significantly exceeding the strong unimodal nnU-Net baseline.”

“UniPercept outperforms existing MLLMs on perceptual-level image understanding and can serve as a plug-and-play reward model for text-to-image generation.”

“incorporating structured sparsity into diffusion models is a promising direction for efficient and expressive long text generation.”

“Our analysis reveals maximum confidence drops of 13.0% (Bootstrap 95% CI: [9.1%, 16.5%]) with strong correlation to actual performance degradation.”

“widgets are compact, context-free micro-interfaces that summarize key information through dense layouts and iconography under strict spatial constraints.”

“The research focuses on establishing baselines for how well LLMs recognize instructional moves.”

“SafeBench-Seq is a homology-clustered, CPU-Only baseline.”

“The research focuses on event-based multi-object tracking.”

“The article is sourced from ArXiv, indicating a peer-reviewed or pre-print research paper.”

“The research focuses on modern trackers and their application in the context of UAV-Anti-UAV.”

“The paper introduces a benchmark and a training-free baseline.”

“The research leverages a 300K-scale dataset.”