{"total":22,"items":[{"citing_arxiv_id":"2607.01649","ref_index":32,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Joint elastic full waveform inversion of multi-component geophone and distributed acoustic sensing data","primary_cat":"physics.geo-ph","submitted_at":"2026-07-02T03:20:18+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"A VSS-based joint FWI framework enables direct multi-deployment inversion of geophone and DAS data, yielding more accurate elastic parameter recovery than single-sensor cases on Marmousi benchmarks when sensors provide complementary information.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.29245","ref_index":22,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"QmDFT for Polycyclic Aromatics: Balancing Embedding Ground-State Fidelity and Experimental Gap Estimation","primary_cat":"quant-ph","submitted_at":"2026-06-28T07:27:53+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"An adaptive damping and DIIS protocol stabilizes QmDFT embedding with hybrid functionals on 10 PAHs, yielding LDA agreement with FCI for ground states and B3LYP agreement with experimental gaps while bypassing explicit excited-state computations.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.25117","ref_index":71,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Feasibility-driven QAOA with penalty scheduling","primary_cat":"quant-ph","submitted_at":"2026-06-23T19:44:00+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Introduces Λ-lr-QAOA and piecewise-ramp QAOA that promote penalty schedules to variational parameters and use a feasibility-driven loss on budget-constrained MWIS satellite planning instances.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.23560","ref_index":19,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"A modified Riemannian Levenberg-Marquardt Algorithm for robust or constraint optimization on manifolds","primary_cat":"math.OC","submitted_at":"2026-06-22T16:29:26+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A robust Riemannian Levenberg-Marquardt algorithm is formulated in block-wise form, with convergence results carried over from prior work and demonstrated via an open-source Manopt.jl implementation on tasks including geodesic regression and Procrustes analysis.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.16575","ref_index":52,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"RepNN: Tackling spectral bias in deep neural networks via parameter reparameterization","primary_cat":"cs.LG","submitted_at":"2026-06-15T11:21:04+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"RepNN reparameterizes the first hidden layer of DNNs to enable adaptive frequency scaling, improving accuracy on oscillatory and multiscale functions with minimal extra cost.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2606.00366","ref_index":18,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"GLENS: Global Search via Learning from Solver Iterates with Diffusion Models","primary_cat":"cs.LG","submitted_at":"2026-05-29T21:09:56+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"GLENS uses diffusion models on solver iterates to generate high-quality and diverse initial guesses for multimodal non-convex optimization, leading to faster solver convergence.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.16060","ref_index":6,"ref_count":2,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Mutually Unbiased Bases for Variational Quantum Initialization: Basis-Union Optimality and Adaptive Family Search","primary_cat":"quant-ph","submitted_at":"2026-05-15T15:26:16+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Complete MUB ensembles are optimal for isotropic Gaussian random-Hamiltonian width among d+1 basis unions, and adaptive MUB-XRot QAOA is non-worse than standard QAOA in 80% of 1500 benchmark cases across MaxCut, MIS, and knapsack.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.14388","ref_index":2,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Multiple mechanisms of rhythm switching in recurrent neural networks with adaptive time constants","primary_cat":"q-bio.NC","submitted_at":"2026-05-14T05:11:54+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Leaky integrator RNNs with adaptive time constants switch between four frequency bands using multiple mechanisms including subpopulation turnover, baseline shifts, and phase reorganization, with high frequencies dominated by short-time-constant neurons.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.10573","ref_index":28,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"A Riemannian quasi-Newton algorithm for optimization with Euclidean bounds","primary_cat":"math.OC","submitted_at":"2026-05-11T13:44:01+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"A Riemannian L-BFGS method with adapted Cauchy-point bound handling outperforms classical interior-point and L-BFGS-B solvers on mixed manifold-plus-bounds problems by orders of magnitude.","context_count":1,"top_context_role":"method","top_context_polarity":"use_method","context_text":"ISSN 1064-8275. doi:10.1137/0916069. Publisher: Society for Industrial and Applied Mathematics. [27] Ciyou Zhu, Richard H. Byrd, Peihuang Lu, and Jorge Nocedal. Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization.ACM Trans. Math. Softw., 23(4):550-560, December 1997. ISSN 0098-3500. doi:10.1145/279232.279236. [28] Richard H. Byrd, Jorge Nocedal, and Robert B. Schnabel. Representations of quasi-Newton matrices and their use in limited memory methods.Mathematical Programming, 63(1):129-156, January 1994. ISSN 1436-4646. doi:10.1007/BF01582063. 14 Riemannian L-BFGS-BA PREPRINT [29] Ronny Bergmann. Manopt.jl: Optimization on manifolds in Julia.Journal of Open Source Software, 7(70):3866,"},{"citing_arxiv_id":"2605.08556","ref_index":2,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Can Revealed Preferences Clarify LLM Alignment and Steering?","primary_cat":"cs.LG","submitted_at":"2026-05-08T23:26:35+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"LLMs show partial internal coherence in medical decisions but frequently fail to accurately report their preferences or adopt user-directed ones via prompting.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2605.04997","ref_index":6,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"DualTCN: A Physics-Constrained Temporal Convolutional Network for 2 Time-Domain Marine CSEM Inversion","primary_cat":"cs.LG","submitted_at":"2026-05-06T14:58:17+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"DualTCN is the first deep-learning model for time-domain marine CSEM inversion that regresses four earth parameters, achieves high accuracy on simulated data, and runs up to 21,000 times faster than classical optimizers.","context_count":1,"top_context_role":"baseline","top_context_polarity":"baseline","context_text":"method has addressed time-domain marine CSEM; (2) all existing methods predict discretised profiles rather than physics-constrained parametric outputs; (3) no systematic encoder comparison (TCN vs. Transformer vs. MLP) exists for this setting; (4) no architecture dedicates a branch to the late-time regime or uses auxiliary physical objectives ford2; (5) ATEM physics-guided strategies have not been transferred to marine CSEM; (6) no calibrated UQ has been demonstrated. DualTCN addresses gaps 1-4 directly, draws on ATEM methodology for gap 5, and provides MC-Dropout UQ with post-hoc calibration for gap 6. 3. Methods 3.1. Earth Model and Synthetic Data We use a one-dimensional three-layer earth model: air (ρair → ∞), seawater (conductivity σ1), and a seafloor half-space (conductivityσ2, extending to infinite depth)."},{"citing_arxiv_id":"2605.03939","ref_index":13,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"The Range of Cumulative XUV Flux on GJ 1132 b","primary_cat":"astro-ph.EP","submitted_at":"2026-05-05T16:29:18+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"GJ 1132 b is estimated to have received at least 50 times the cumulative XUV flux of modern Earth with over 95% probability across models, supporting its classification as an atmosphere-free world.","context_count":1,"top_context_role":"background","top_context_polarity":"unclear","context_text":"ference of the Ribas et al. (2005) model parameters. As shown in Table 1, only the X-ray luminosity has been directly measured, so we must rely on a scaling rela- tionship to calculate the XUV luminosity,L EU V . For this calculation, we use the Sanz-Forcada et al. (2025) model: log(LEU V ) = (0.821±0.041)C X + (28.16±0.05),(12) where CX = log(LX)−27.44,(13) when all luminosities are expressed in units of ergs/s. We first build theL XU V distribution via 10 4 draws from the observedL X distribution, and then compute an LEU V value from it, including the inherent uncertainties in the Sanz-Forcada et al. (2025) model. The result is shown in the left panel of Fig. 5, where the best fit and uncertainty areL XU V = (2."},{"citing_arxiv_id":"2605.03906","ref_index":18,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Variational Joint Magnetometry and Gradiometry on Dipolar Spin Chains","primary_cat":"quant-ph","submitted_at":"2026-05-05T15:59:22+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"Variational optimization on dipolar spin chains reaches 0.92 of the quantum Fisher information benchmark for joint magnetometry and gradiometry, delivering a 4.2x advantage over the standard quantum limit.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.15855","ref_index":14,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"PISP: Projected-Space Inference of Stellar Parameters","primary_cat":"astro-ph.SR","submitted_at":"2026-04-17T09:05:18+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"PISP projects high-dimensional spectra into optimized subspaces using PCA or active subspaces plus L1 selection to raise accuracy and speed of stellar parameter inference over standard methods.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2604.12505","ref_index":41,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Data-driven Learning of LPV Surrogate Models of Fuel Sloshing","primary_cat":"eess.SY","submitted_at":"2026-04-14T09:28:23+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":4.0,"formal_verification":"none","one_line_summary":"An open-source Jax-based SPH simulator generates training data for LPV state-space surrogates that approximate fuel sloshing dynamics and enable 100x faster closed-loop spacecraft simulations under zero gravity.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2603.21689","ref_index":49,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Implementation of a shooting technique for quantum optimal control on spin qudits","primary_cat":"quant-ph","submitted_at":"2026-03-23T08:22:19+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"A shooting technique yields smooth control pulses for quantum gates on spin qudits that are faster than GRAPE, with the advantage growing as system dimension increases, shown in numerical simulations inspired by single molecule magnets.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2603.10992","ref_index":50,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"A Tutorial Review of Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches","primary_cat":"stat.ML","submitted_at":"2026-03-11T17:20:28+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":3.0,"formal_verification":"none","one_line_summary":"Bayesian optimization with Gaussian processes unifies minimization, single-point saddle searches, and double-ended path searches on potential energy surfaces through a shared six-step surrogate loop using derivative observations and inverse-distance kernels.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2602.23010","ref_index":10,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Helmlab: A Two-Space Family of Analytical, Data-Driven Color Spaces for UI Design Systems","primary_cat":"cs.GR","submitted_at":"2026-02-26T13:52:42+00:00","verdict":"CONDITIONAL","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"Helmlab defines MetricSpace and GenSpace as analytical data-driven color spaces that cut color difference error by 23% versus CIEDE2000 on primary benchmarks while outperforming OKLab on gradient tasks.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2511.20514","ref_index":20,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Real-time 3D Ultrasonic Needle Tracking with a Photoacoustic Beacon","primary_cat":"physics.med-ph","submitted_at":"2025-11-25T17:19:23+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":6.0,"formal_verification":"none","one_line_summary":"A photoacoustic beacon in the needle bevel allows real-time 3D ultrasonic tracking with sub-2 mm accuracy in water and tissue phantoms, cutting biopsy failure rates by 35% in a clinician usability study.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"2507.23679","ref_index":48,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Swap Network Augmented Ans\\\"atze on Arbitrary Connectivity","primary_cat":"quant-ph","submitted_at":"2025-07-31T15:56:28+00:00","verdict":"UNVERDICTED","verdict_confidence":"LOW","novelty_score":5.0,"formal_verification":"none","one_line_summary":"By augmenting quantum circuit ansatze with optimized swap networks, the work achieves better performance in ground-state energy calculations using fewer resources on devices with arbitrary qubit connectivity.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"1909.01066","ref_index":134,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"Language Models as Knowledge Bases?","primary_cat":"cs.CL","submitted_at":"2019-09-03T11:11:08+00:00","verdict":"ACCEPT","verdict_confidence":"LOW","novelty_score":7.0,"formal_verification":"none","one_line_summary":"BERT stores relational knowledge extractable via cloze queries without fine-tuning and matches supervised baselines on open-domain QA tasks.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null},{"citing_arxiv_id":"1907.10121","ref_index":121,"ref_count":1,"confidence":0.88,"is_internal_anchor":false,"paper_title":"SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python","primary_cat":"cs.MS","submitted_at":"2019-07-23T20:31:36+00:00","verdict":"ACCEPT","verdict_confidence":"MODERATE","novelty_score":2.0,"formal_verification":"none","one_line_summary":"SciPy 1.0 documents a mature open-source library that has become the de facto standard for scientific algorithms in Python with broad adoption across research projects.","context_count":0,"top_context_role":null,"top_context_polarity":null,"context_text":null}],"limit":50,"offset":0}