“Unlike prior single-paradigm approaches, which achieve <75% accuracy on out-of-distribution datasets, our method maintains 86.8% average accuracy across seven diverse test sets...”

“To address these limitations, we propose HyperJoin, a large language model (LLM)-augmented Hypergraph framework for Joinable table discovery.”

“Now i have been thinking that LLM models based on the transformer architecture are essentially an overglorified classifier during training (forced prediction of the next token at every step).”

“The framework combines hierarchical deformation planning with neural tracking, ensuring reliable performance in both global deformation synthesis and local deformation tracking.”

“STAgent effectively preserves its general capabilities.”

“PRISM addresses the challenge through a learnable tree-based partitioning of the signal.”

“The paper identifies an anomalous glassy regime where relaxation times are orders of magnitude faster than predicted, and shows that dynamics are partly accelerated by laser light absorption. The 'time-length scale superposition principle' is a key finding.”

“HiGR delivers consistent improvements in both offline evaluations and online deployment. Specifically, it outperforms state-of-the-art methods by over 10% in offline recommendation quality with a 5x inference speedup, while further achieving a 1.22% and 1.73% increase in Average Watch Time and Average Video Views in online A/B tests.”

“EchoVidia surpasses recent VT2A models by 40.7% in controllability and 12.5% in perceptual quality.”

“The proposed framework achieves superior performance over conventional sensing methods with reduced sensing power.”

“CREPES-X achieves RMSE of 0.073m and 1.817° in real-world datasets, demonstrating robustness to up to 90% bearing outliers.”

“BatteryAgent effectively corrects misclassifications on hard boundary samples, achieving an AUROC of 0.986, which significantly outperforms current state-of-the-art methods.”

“The proposed HOOA achieves significant improvements, which reduces average task completion delay by 2.5% and average energy consumption by 3.1% compared with the best-performing benchmark approach and state-of-the-art DRL algorithm, respectively.”

“The dataset incorporates 12K tactile-enhanced episodes and 20K mobile manipulation trajectories.”

“PAM supports a 300-frame history window while maintaining high inference speed (above 20Hz).”

“The proposed system consistently outperformed flat multi-class classifiers and pre-trained self-supervised models.”

“The paper proposes a Layer-by-Layer Hierarchical Attention Network (LLHA-Net) to enhance the precision of feature point matching by addressing the issue of outliers.”

“DLCM reallocates roughly one-third of inference compute into a higher-capacity reasoning backbone, achieving a +2.69% average improvement across 12 zero-shot benchmarks under matched inference FLOPs.”

“HUMOR employs a hierarchical, multi-path Chain-of-Thought (CoT) to enhance reasoning diversity and a pairwise reward model for capturing subjective humor.”

“The model achieves 25.96 dB PSNR and 0.8375 SSIM on the test set, demonstrating its effectiveness in compressing low-resolution video while maintaining good perceptual quality.”

“The paper derives a novel recursion relationship across depth which extends the eligibility traces of E-prop to deeper layers.”

“Analyzing 1.4 million customer transactions across seven markets, our approach reduces false positive and false negative rates to 4.64% and 11.07%, substantially outperforming single-institution models. The framework prevents 79.25% of potential losses versus 49.41% under fixed-rule policies.”

“The paper introduces two complementary high-order strategies for triangular elements: a reduced quadrilateralization approach and a triangle based spectral element method based on Dubiner polynomials.”

“DRL-TH outperforms existing methods in various crowded environments. We also implemented DRL-TH control policy on a real UGV and showed that it performed well in real world scenarios.”

“ARM learns to adaptively fuse hierarchical features. It employs a semantically-guided cross-attention block, using robust deep features (K, V) to select and refine detail-rich shallow features (Q), followed by a self-attention block.”

“The paper introduces a suite of performance optimizations, including interleaved pipeline scheduling, attention-aware data scheduling for long-sequence training, hierarchical and overlapped communication for expert parallelism, and DVM-based operator fusion.”

“The paper explains how the hierarchical hull of a pair of points in any colorable hierarchically hyperbolic space is quasi-isometric to a finite CAT(0) cube complex of bounded dimension.”

“Key findings demonstrate that sub-goal decomposition and irrelevant premise filtering critically influence final problem-solving accuracy, whereas Chain-of-Thought prompting unexpectedly degrades performance in some tasks.”

“The paper proposes two original algorithms: a generic polynomial-time sequential algorithm with theoretical guarantees and an extension of the General Yankee Swap.”

“The paper argues that the optimal substrate for motion planning is not natural language, but a learned, motion-aligned concept space.”

“The paper introduces evidence tokens for evidence grounding, which emphasize event-level visual semantic capture beyond the focus on timestamp representation.”

“The proposed loss introduces learnable class prototypes and equilibrates gradients contributed by different classes at each hierarchical level, ensuring that each hierarchical class contributes equally to the loss computation in every mini-batch.”

“HERO Sign achieves throughput improvements of 1.28-3.13, 1.28-2.92, and 1.24-2.60 under the SPHINCS+ 128f, 192f, and 256f parameter sets on RTX 4090.”

“The paper provides explicit code parameters and properties as well as some additional bounds on parameters such as rank and distance.”

“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.”

“MS-SSM enhances memory efficiency and long-range modeling.”

“The proposed preconditioners significantly accelerate the convergence of iterative solvers compared to existing methods.”

“The paper derives precise masses and the complete set of its fundamental parameters for the three components, and introduces a new orbital solution, and a new dynamical parallax.”

“TabMixNN provides a unified interface for researchers to leverage deep learning while maintaining the interpretability and theoretical grounding of classical mixed-effects models.”

“BOAD outperforms single-agent and manually designed multi-agent systems. On SWE-bench-Live, featuring more recent and out-of-distribution issues, our 36B system ranks second on the leaderboard at the time of evaluation, surpassing larger models such as GPT-4 and Claude.”

“The Bayesian joint model consistently outperforms conventional two-stage approaches in terms of parameter estimation accuracy and predictive performance.”

“The proposed Agentic AI framework demonstrates consistent improvements across key performance indicators, including higher throughput, improved cell-edge performance, and reduced latency across different slices.”

“PanCAN learns multi-order neighborhood relationships at each scale by combining random walks with an attention mechanism.”

“FRoD matches full model fine-tuning in accuracy, while using only 1.72% of trainable parameters under identical training budgets.”

“The method starts by identifying texts of strong semantic similarity as it searches for dense clusters in LLM embedding space.”

“The paper introduces the Refined Aesthetic Description (RAD) dataset and the ArtQuant framework, achieving state-of-the-art performance while using fewer training epochs.”

“ReSUs offer (i) a principled framework for modeling sensory circuits and (ii) a biologically grounded, backpropagation-free paradigm for constructing deep self-supervised neural networks.”

“The paper formalizes commitment as inference under a mixture of reverse- and forward-Kullback-Leibler (KL) objectives.”

“The proposed framework achieves an overall accuracy of 89.72% and a macro-average F1-score of 85.46%. Notably, it attains an F1- score of 61.7% for the challenging N1 stage, demonstrating a substantial improvement over previous methods on the SleepEDF datasets.”

“The paper derives numerically ``exact'' hierarchical equations of motion (MO-HEOM) from a MO framework.”