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8b0a730cf07d5592b8bd892dcb2d9c4b939459de1179d20d7a42c92b143de286 | 2026-01-23T00:00:00-05:00 | LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback | arXiv:2601.15280v1 Announce Type: cross Abstract: Providing timely, targeted, and multimodal feedback helps students quickly correct errors, build deep understanding and stay motivated, yet making it at scale remains a challenge. This study introduces a real-time AI-facilitated multimodal feedback system that integrate... | https://arxiv.org/abs/2601.15280 | Academic Papers | svg |
82f2cd497dac0e4f66973e729cfbfdb45ddfc2a3e141f0fd6ad8da93c2634f4a | 2026-01-23T00:00:00-05:00 | Ecosystem Competition and Cross-Market Subsidization: A Dynamic Theory of Platform Pricing | arXiv:2601.15303v1 Announce Type: cross Abstract: Platform giants in China have operated with persistently compressed margins in highly concentrated markets for much of the past decade, despite market shares exceeding 60\% in core segments. Standard theory predicts otherwise: either the weaker firm exits, or survivors ... | https://arxiv.org/abs/2601.15303 | Academic Papers | svg |
a54de7f3c7ef6e308629aeabf9fa6b897c065e3a9c1866fb22a88678d7d580bd | 2026-01-23T00:00:00-05:00 | An Explainable Market Integrity Monitoring System with Multi-Source Attention Signals and Transparent Scoring | arXiv:2601.15304v1 Announce Type: cross Abstract: Market integrity monitoring is difficult because suspicious price/volume behavior can arise from many benign mechanisms, while modern detection systems often rely on opaque models that are hard to audit and communicate. We present AIMM-X, an explainable monitoring pipel... | https://arxiv.org/abs/2601.15304 | Academic Papers | svg |
b81a8d82eef271e35161f8b42345899d8c6f44d417a80fd110f07378dd7b1a39 | 2026-01-23T00:00:00-05:00 | Mind the Gap: Why Neural Memory Fails Under Semantic Density | arXiv:2601.15313v1 Announce Type: cross Abstract: The brain solves a problem that current AI architectures struggle to manage: storing specific episodic facts without corrupting general semantic knowledge. Neuroscience explains this through Complementary Learning Systems theory - a fast hippocampal system for episodic ... | https://arxiv.org/abs/2601.15313 | Academic Papers | svg |
c9910c26cd6609cd3186e5be7ee8c0fb3009df85d2f23ac254fc477d08293db0 | 2026-01-23T00:00:00-05:00 | Beyond the Einstein-Bohr Debate: Cognitive Complementarity and the Emergence of Quantum Intuition | arXiv:2601.15314v1 Announce Type: cross Abstract: Recent high-precision experimental confirmations of quantum complementarity have revitalized foundational debates about measurement, description, and realism. This article argues that complementarity is most productively interpreted as an epistemic principle--constraini... | https://arxiv.org/abs/2601.15314 | Academic Papers | svg |
73003302b862273cb552953640f8f657722a90d562af40aa687c054e26e574d7 | 2026-01-23T00:00:00-05:00 | The Impossibility of Cohesion Without Fragmentation | arXiv:2601.15317v1 Announce Type: cross Abstract: Most models in game theory and network formation implicitly assume that relations between agents are feasible whenever incentives are aligned or interaction opportunities exist. Under this premise analytical attention is directed toward equilibrium efficiency or probabi... | https://arxiv.org/abs/2601.15317 | Academic Papers | svg |
fa393f1355cb655026bbda07a994435d675a9fb717f2e05292fdf3f05d4acc1a | 2026-01-23T00:00:00-05:00 | Large Language Models as Simulative Agents for Neurodivergent Adult Psychometric Profiles | arXiv:2601.15319v1 Announce Type: cross Abstract: Adult neurodivergence, including Attention-Deficit/Hyperactivity Disorder (ADHD), high-functioning Autism Spectrum Disorder (ASD), and Cognitive Disengagement Syndrome (CDS), is marked by substantial symptom overlap that limits the discriminant sensitivity of standard p... | https://arxiv.org/abs/2601.15319 | Academic Papers | svg |
3fac7fd86220e8d85d10cebc6317ddc7216aa36f5cef946dddaecad3e6f4e8a6 | 2026-01-23T00:00:00-05:00 | Analysis of the Ventriloquism Aftereffect Using Network Theory Techniques | arXiv:2601.15321v1 Announce Type: cross Abstract: Ventriloquism After-Effect is the phenomenon where sustained exposure to the ventriloquist illusion causes a change in unisensory auditory localization towards the location where the visual stimulus was present. We investigate the recalibration in EEG networks that caus... | https://arxiv.org/abs/2601.15321 | Academic Papers | svg |
0e074156b7e729492a0633d3ff368a18178b628f73a1a0ffeb8ce1b2f2a65461 | 2026-01-23T00:00:00-05:00 | ECGomics: An Open Platform for AI-ECG Digital Biomarker Discovery | arXiv:2601.15326v1 Announce Type: cross Abstract: Background: Conventional electrocardiogram (ECG) analysis faces a persistent dichotomy: expert-driven features ensure interpretability but lack sensitivity to latent patterns, while deep learning offers high accuracy but functions as a black box with high data dependenc... | https://arxiv.org/abs/2601.15326 | Academic Papers | svg |
7827f4eaf2306a483925f955f8029631444ab885ebda345f113dea0899095324 | 2026-01-23T00:00:00-05:00 | Learning Discrete Successor Transitions in Continuous Attractor Networks: Emergence, Limits, and Topological Constraints | arXiv:2601.15336v1 Announce Type: cross Abstract: Continuous attractor networks (CANs) are a well-established class of models for representing low-dimensional continuous variables such as head direction, spatial position, and phase. In canonical spatial domains, transitions along the attractor manifold are driven by co... | https://arxiv.org/abs/2601.15336 | Academic Papers | svg |
9e1c1d3746d79c79b33dfc5068fbdde90a47f394e7b212a5fb0a23a8af71087a | 2026-01-23T00:00:00-05:00 | Learning Nonlinear Heterogeneity in Physical Kolmogorov-Arnold Networks | arXiv:2601.15340v1 Announce Type: cross Abstract: Physical neural networks typically train linear synaptic weights while treating device nonlinearities as fixed. We show the opposite - by training the synaptic nonlinearity itself, as in Kolmogorov-Arnold Network (KAN) architectures, we yield markedly higher task perfor... | https://arxiv.org/abs/2601.15340 | Academic Papers | svg |
6360d8a5a5a2d57c23b3b21c64636b8d282a4ccc03684a53f6d305a8645fc7e1 | 2026-01-23T00:00:00-05:00 | OmniSpectra: A Unified Foundation Model for Native Resolution Astronomical Spectra | arXiv:2601.15351v1 Announce Type: cross Abstract: We present OmniSpectra, the first native-resolution foundation model for astronomy spectra. Unlike traditional models, which are limited to fixed-length input sizes or configurations, OmniSpectra handles spectra of any length at their original size, without resampling o... | https://arxiv.org/abs/2601.15351 | Academic Papers | svg |
830f0b480a5e71f99ea51a75b2a4c99f1b64f2ed367bdfb9df7513d637281ac5 | 2026-01-23T00:00:00-05:00 | Statistical Reinforcement Learning in the Real World: A Survey of Challenges and Future Directions | arXiv:2601.15353v1 Announce Type: cross Abstract: Reinforcement learning (RL) has achieved remarkable success in real-world decision-making across diverse domains, including gaming, robotics, online advertising, public health, and natural language processing. Despite these advances, a substantial gap remains between RL... | https://arxiv.org/abs/2601.15353 | Academic Papers | svg |
a3b5bcd7fa12289c7cf0efdec00fd3608c02d43852a1295dab615c8995b71a47 | 2026-01-23T00:00:00-05:00 | Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing | arXiv:2601.15356v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Quality Assessment (IQA). However, existing RL-based IQA models typically rely on coarse-grained global views, failing to capture s... | https://arxiv.org/abs/2601.15356 | Academic Papers | svg |
5028ebf1976975bde06282b04fceba26b9be97fe7dadacabdb52e473f4625fd6 | 2026-01-23T00:00:00-05:00 | High-Fidelity 3D Tooth Reconstruction by Fusing Intraoral Scans and CBCT Data via a Deep Implicit Representation | arXiv:2601.15358v1 Announce Type: cross Abstract: High-fidelity 3D tooth models are essential for digital dentistry, but must capture both the detailed crown and the complete root. Clinical imaging modalities are limited: Cone-Beam Computed Tomography (CBCT) captures the root but has a noisy, low-resolution crown, whil... | https://arxiv.org/abs/2601.15358 | Academic Papers | svg |
d689a25be5b66b0624f301188a52d6d8daaa0b21677e35b8e2ec7794c19efa4d | 2026-01-23T00:00:00-05:00 | Robust X-Learner: Breaking the Curse of Imbalance and Heavy Tails via Robust Cross-Imputation | arXiv:2601.15360v1 Announce Type: cross Abstract: Estimating Heterogeneous Treatment Effects (HTE) in industrial applications such as AdTech and healthcare presents a dual challenge: extreme class imbalance and heavy-tailed outcome distributions. While the X-Learner framework effectively addresses imbalance through cro... | https://arxiv.org/abs/2601.15360 | Academic Papers | svg |
1bf67e7ee8fcb87a1b9e791e45453f692798e3fe5e6f6834058910a492d3c981 | 2026-01-23T00:00:00-05:00 | USDs: A universal stabilizer decoder framework using symmetry | arXiv:2601.15361v1 Announce Type: cross Abstract: Quantum error correction is indispensable to achieving reliable quantum computation. When quantum information is encoded redundantly, a larger Hilbert space is constructed using multiple physical qubits, and the computation is performed within a designated subspace. Whe... | https://arxiv.org/abs/2601.15361 | Academic Papers | svg |
aa98b51e14fd9ab933786946a5527a55f2743f2b1cc35e9b8502c51192252e96 | 2026-01-23T00:00:00-05:00 | Non-Stationary Functional Bilevel Optimization | arXiv:2601.15363v1 Announce Type: cross Abstract: Functional bilevel optimization (FBO) provides a powerful framework for hierarchical learning in function spaces, yet current methods are limited to static offline settings and perform suboptimally in online, non-stationary scenarios. We propose SmoothFBO, the first alg... | https://arxiv.org/abs/2601.15363 | Academic Papers | svg |
12ed5066a284147d3f81a92a6ee27fff8f93d963aed981052e1056c830e8f86e | 2026-01-23T00:00:00-05:00 | OpenVision 3: A Family of Unified Visual Encoder for Both Understanding and Generation | arXiv:2601.15369v1 Announce Type: cross Abstract: This paper presents a family of advanced vision encoder, named OpenVision 3, that learns a single, unified visual representation that can serve both image understanding and image generation. Our core architecture is simple: we feed VAE-compressed image latents to a ViT ... | https://arxiv.org/abs/2601.15369 | Academic Papers | svg |
75ac4888f2e98ff2fe51ae1ddbea37d29c5ff3f7bcc50c3cb7fb2808ea5d2dfb | 2026-01-23T00:00:00-05:00 | The computational two-way quantum capacity | arXiv:2601.15393v1 Announce Type: cross Abstract: Quantum channel capacities are fundamental to quantum information theory. Their definition, however, does not limit the computational resources of sender and receiver. In this work, we initiate the study of computational quantum capacities. These quantify how much infor... | https://arxiv.org/abs/2601.15393 | Academic Papers | svg |
57985ae0d8c5c24effee688bf76c94434cc72b1ff4c23a2b2f5bdc1f5f396cb8 | 2026-01-23T00:00:00-05:00 | ISAC-over-NTN: HAPS-UAV Framework for Post-Disaster Responsive 6G Networks | arXiv:2601.15422v1 Announce Type: cross Abstract: In disaster scenarios, ensuring both reliable communication and situational awareness becomes a critical challenge due to the partial or complete collapse of terrestrial networks. This paper proposes an integrated sensing and communication (ISAC) over non-terrestrial ne... | https://arxiv.org/abs/2601.15422 | Academic Papers | svg |
c0d30a92dbba18d18318d554dac34fcd1e10b5ed8a1e545fd7dfa519aa69c384 | 2026-01-23T00:00:00-05:00 | Low-Dimensional Adaptation of Rectified Flow: A New Perspective through the Lens of Diffusion and Stochastic Localization | arXiv:2601.15500v1 Announce Type: cross Abstract: In recent years, Rectified flow (RF) has gained considerable popularity largely due to its generation efficiency and state-of-the-art performance. In this paper, we investigate the degree to which RF automatically adapts to the intrinsic low dimensionality of the suppor... | https://arxiv.org/abs/2601.15500 | Academic Papers | svg |
4752677c96c1046df0c71ae7c2e4b1e725889fd545b0532e7a5c1ccd7b2a2d73 | 2026-01-23T00:00:00-05:00 | Applicability and Limitation Analysis of PMU Data and Phasor Concept for Low- and High- Frequency Oscillations | arXiv:2601.15529v1 Announce Type: cross Abstract: Phasor Measurement Units (PMUs) convert high-speed waveform data into low-speed phasor data, which are fundamental to wide-area monitoring and control in power systems, with oscillation detection and localization among their most prominent applications. However, represe... | https://arxiv.org/abs/2601.15529 | Academic Papers | svg |
48903d2185e4f902d0ded2df5eb84bb6f9fed4ae0017ab77c9d6898aba8d2277 | 2026-01-23T00:00:00-05:00 | A Machine Vision Approach to Preliminary Skin Lesion Assessments | arXiv:2601.15539v1 Announce Type: cross Abstract: Early detection of malignant skin lesions is critical for improving patient outcomes in aggressive, metastatic skin cancers. This study evaluates a comprehensive system for preliminary skin lesion assessment that combines the clinically established ABCD rule of dermosco... | https://arxiv.org/abs/2601.15539 | Academic Papers | svg |
aa68a7cbe6dc17d100809d3003a8893746aca15a3b355142002fb481a035c3c3 | 2026-01-23T00:00:00-05:00 | Stabilizing Welfare-Maximizing Decisions via Endogenous Transfers | arXiv:2601.15563v1 Announce Type: cross Abstract: Many multiagent systems rely on collective decision-making among self-interested agents, which raises deep questions about coalition formation and stability. We study social choice with endogenous, outcome-contingent transfers, where agents voluntarily form contracts th... | https://arxiv.org/abs/2601.15563 | Academic Papers | svg |
394d7fbbef7c30884e70b79d74648012520961ed1c8650aa1cdb2f6297cc36e3 | 2026-01-23T00:00:00-05:00 | FUGC: Benchmarking Semi-Supervised Learning Methods for Cervical Segmentation | arXiv:2601.15572v1 Announce Type: cross Abstract: Accurate segmentation of cervical structures in transvaginal ultrasound (TVS) is critical for assessing the risk of spontaneous preterm birth (PTB), yet the scarcity of labeled data limits the performance of supervised learning approaches. This paper introduces the Feta... | https://arxiv.org/abs/2601.15572 | Academic Papers | svg |
6dd4e5f819507c81c9d0adb52c8a8bc3a1b88ef4abddc5d4f5549480adbe0ea1 | 2026-01-23T00:00:00-05:00 | Screening for Choice Sets | arXiv:2601.15580v1 Announce Type: cross Abstract: We study a screening problem in which an agent privately observes a set of feasible technologies and can strategically disclose only a subset to the principal. The principal then takes an action whose payoff consequences for both players are publicly known. Under the as... | https://arxiv.org/abs/2601.15580 | Academic Papers | svg |
1738a446c87082a42fab20c04d48971fb38f510c0395dcc675b475e806137c1e | 2026-01-23T00:00:00-05:00 | Does 6G Need a New Waveform: Comparing Zak-OTFS with CP-OFDM | arXiv:2601.15602v1 Announce Type: cross Abstract: Across the world, there is growing interest in new waveforms, Zak-OTFS in particular, and over-the-air implementations are starting to appear. The choice between OFDM and Zak-OTFS is not so much a choice between waveforms as it is an architectural choice between prevent... | https://arxiv.org/abs/2601.15602 | Academic Papers | svg |
ebd7554a477129c3a8cef6533ba889c6ef80d694dc571f5a3379d7c537561846 | 2026-01-23T00:00:00-05:00 | On the Nonasymptotic Scaling Guarantee of Hyperparameter Estimation in Inhomogeneous, Weakly-Dependent Complex Network Dynamical Systems | arXiv:2601.15603v1 Announce Type: cross Abstract: Hierarchical Bayesian models are increasingly used in large, inhomogeneous complex network dynamical systems by modeling parameters as draws from a hyperparameter-governed distribution. However, theoretical guarantees for these estimates as the system size grows have be... | https://arxiv.org/abs/2601.15603 | Academic Papers | svg |
ce440d91b75be33280ba9f992f4028192e26e0104a70f555b3e865c67945232a | 2026-01-23T00:00:00-05:00 | Machine Failure Detection Based on Projected Quantum Models | arXiv:2601.15641v1 Announce Type: cross Abstract: Detecting machine failures promptly is of utmost importance in industry for maintaining efficiency and minimizing downtime. This paper introduces a failure detection algorithm based on quantum computing and a statistical change-point detection approach. Our method lever... | https://arxiv.org/abs/2601.15641 | Academic Papers | svg |
ab8d2ccf061b82c9a0e39fba62aa9d42ede6e973874966135c9349600f21f2b4 | 2026-01-23T00:00:00-05:00 | Algebraic Statistics in OSCAR | arXiv:2601.15807v1 Announce Type: cross Abstract: We introduce the AlgebraicStatistics section of the OSCAR computer algebra system. We give an overview of its extensible design and highlight its features including serialization of data types for sharing results and creating databases, and state-of-the-art implicitizat... | https://arxiv.org/abs/2601.15807 | Academic Papers | svg |
20b2072b219b9231833aa49de70df4ef403763abb749e3c0512f9a9ff1a5d61c | 2026-01-23T00:00:00-05:00 | Quantum Coherence Spaces Revisited: A von Neumann (Co)Algebraic Approach | arXiv:2601.15832v1 Announce Type: cross Abstract: We describe a categorical model of MALL (Multiplicative Additive Linear Logic) inspired by the Heisenberg-Schr\"odinger duality of finite-dimensional quantum theory. Proofs of formulas with positive logical polarity correspond to CPTP (completely positive trace-preservi... | https://arxiv.org/abs/2601.15832 | Academic Papers | svg |
0854b4a25857e5d4a202aa28431e97f2c06cd45e477b893f1f7fffec00bd81b4 | 2026-01-23T00:00:00-05:00 | A Stabilized Hybrid Active Noise Control Algorithm of GFANC and FxNLMS with Online Clustering | arXiv:2601.15889v1 Announce Type: cross Abstract: The Filtered-x Normalized Least Mean Square (FxNLMS) algorithm suffers from slow convergence and a risk of divergence, although it can achieve low steady-state errors after sufficient adaptation. In contrast, the Generative Fixed-Filter Active Noise Control (GFANC) meth... | https://arxiv.org/abs/2601.15889 | Academic Papers | svg |
7aa074868e394471bdac7ab1c2b10f3780de87df7ce2a395dcd5898037ef8b13 | 2026-01-23T00:00:00-05:00 | Progressive Power Homotopy for Non-convex Optimization | arXiv:2601.15915v1 Announce Type: cross Abstract: We propose a novel first-order method for non-convex optimization of the form $\max_{\bm{w}\in\mathbb{R}^d}\mathbb{E}_{\bm{x}\sim\mathcal{D}}[f_{\bm{w}}(\bm{x})]$, termed Progressive Power Homotopy (Prog-PowerHP). The method applies stochastic gradient ascent to a surro... | https://arxiv.org/abs/2601.15915 | Academic Papers | svg |
f2b6ae748185a87aaf0bcad0bce8d3d58d83f7e67f6bb13134e16c7d7e453c38 | 2026-01-23T00:00:00-05:00 | An Efficient Algorithm to Generate all Labeled Triangle-free Graphs with a given Graphical Degree Sequence | arXiv:2601.15943v1 Announce Type: cross Abstract: We extend our previous algorithm that generates all labeled graphs with a given graphical degree sequence to generate all labeled triangle-free graphs with a given graphical degree sequence. The algorithm uses various pruning techniques to avoid having to first generate... | https://arxiv.org/abs/2601.15943 | Academic Papers | svg |
364b36d548651b590b73e38b6c0ae714bed894a4a6d41f77dd3c8c16173375d5 | 2026-01-23T00:00:00-05:00 | Performance Scaling Laws for PD Array-based Receivers in IM/DD Optical Wireless Communication Systems | arXiv:2601.15973v1 Announce Type: cross Abstract: We study the performance scaling laws for electrical-domain combining in photodetector (PD) array-based receivers employing intensity modulation and direct detection, taking into account the inherent square-law relationship between the optical and electrical received po... | https://arxiv.org/abs/2601.15973 | Academic Papers | svg |
c90fe58e1efdbfc2d00c02f9460c934ca93bf33a5013cc49c52ff12418aba250 | 2026-01-23T00:00:00-05:00 | Time-Optimal Switching Surfaces for Triple Integrator under Full Box Constraints | arXiv:2601.16003v1 Announce Type: cross Abstract: Time-optimal control for triple integrator under full box constraints is a fundamental problem in the field of optimal control, which has been widely applied in the industry. However, scenarios involving asymmetric constraints, non-stationary boundary conditions, and ac... | https://arxiv.org/abs/2601.16003 | Academic Papers | svg |
5cdf0f837a348ff1b3b8077826d91b5bf5fd68b1f41d1df35a5c6e95dd36963e | 2026-01-23T00:00:00-05:00 | Wigner's Friend as a Circuit: Inter-Branch Communication Witness Benchmarks on Superconducting Quantum Hardware | arXiv:2601.16004v1 Announce Type: cross Abstract: We implement and benchmark on IBM Quantum hardware the circuit family proposed by Violaris for estimating operational inter-branch communication witnesses, defined as correlations in classical measurement records produced by compiled Wigner's-friend-style circuits. We r... | https://arxiv.org/abs/2601.16004 | Academic Papers | svg |
88b2ebb1703ea6dfe387d35b728db3340c1d1901c21032c9c8957a3b134323dd | 2026-01-23T00:00:00-05:00 | THOR: A Versatile Foundation Model for Earth Observation Climate and Society Applications | arXiv:2601.16011v1 Announce Type: cross Abstract: Current Earth observation foundation models are architecturally rigid, struggle with heterogeneous sensors and are constrained to fixed patch sizes. This limits their deployment in real-world scenarios requiring flexible computeaccuracy trade-offs. We propose THOR, a "c... | https://arxiv.org/abs/2601.16011 | Academic Papers | svg |
a2ec204618f3d83af7e11fb63fac3f116bdf991946c9e3f23f42f5167fd2b106 | 2026-01-23T00:00:00-05:00 | Timbre-Aware LLM-based Direct Speech-to-Speech Translation Extendable to Multiple Language Pairs | arXiv:2601.16023v1 Announce Type: cross Abstract: Direct Speech-to-Speech Translation (S2ST) has gained increasing attention for its ability to translate speech from one language to another, while reducing error propagation and latency inherent in traditional cascaded pipelines. However, existing direct S2ST systems co... | https://arxiv.org/abs/2601.16023 | Academic Papers | svg |
851fc6116edabff478ffaaf3c10dd299ca42955d1b217d5fd72342ef1ca10c05 | 2026-01-23T00:00:00-05:00 | Risk reversal for least squares estimators under nested convex constraints | arXiv:2601.16041v1 Announce Type: cross Abstract: In constrained stochastic optimization, one naturally expects that imposing a stricter feasible set does not increase the statistical risk of an estimator defined by projection onto that set. In this paper, we show that this intuition can fail even in canonical settings... | https://arxiv.org/abs/2601.16041 | Academic Papers | svg |
12eeefd366407399088dac93f78192b1d12afcf98b598710b0d51eacfb6768d5 | 2026-01-23T00:00:00-05:00 | Phi-SegNet: Phase-Integrated Supervision for Medical Image Segmentation | arXiv:2601.16064v1 Announce Type: cross Abstract: Deep learning has substantially advanced medical image segmentation, yet achieving robust generalization across diverse imaging modalities and anatomical structures remains a major challenge. A key contributor to this limitation lies in how existing architectures, rangi... | https://arxiv.org/abs/2601.16064 | Academic Papers | svg |
4d5e33bfa6172468941c3b03f923d2caf0f0647fb496eef85bb3c6be6389208c | 2026-01-23T00:00:00-05:00 | On damage of interpolation to adversarial robustness in regression | arXiv:2601.16070v1 Announce Type: cross Abstract: Deep neural networks (DNNs) typically involve a large number of parameters and are trained to achieve zero or near-zero training error. Despite such interpolation, they often exhibit strong generalization performance on unseen data, a phenomenon that has motivated exten... | https://arxiv.org/abs/2601.16070 | Academic Papers | svg |
1085929e9cc290f0ff3956325e392d7a529576ed39cb66c889f9465a2f781f2d | 2026-01-23T00:00:00-05:00 | Algorithms for Algebraic and Arithmetic Attributes of Hypergeometric Functions | arXiv:2601.16105v1 Announce Type: cross Abstract: We discuss algorithms for arithmetic properties of hypergeometric functions. Most notably, we are able to compute the p-adic valuation of a hypergeometric function on any disk of radius smaller than the p-adic radius of convergence. This we use, building on work of Chri... | https://arxiv.org/abs/2601.16105 | Academic Papers | svg |
202020747611be872ab8825b44e155ee2bf60f9f04e7661e82d1306cf919726a | 2026-01-23T00:00:00-05:00 | Synthetic Augmentation in Imbalanced Learning: When It Helps, When It Hurts, and How Much to Add | arXiv:2601.16120v1 Announce Type: cross Abstract: Imbalanced classification, where one class is observed far less frequently than the other, often causes standard training procedures to prioritize the majority class and perform poorly on rare but important cases. A classic and widely used remedy is to augment the minor... | https://arxiv.org/abs/2601.16120 | Academic Papers | svg |
95586bfb1c6a174967d8b5722b887e916f8bf3f7dd8a52579ef3e35cc67636c8 | 2026-01-23T00:00:00-05:00 | Beyond Predictive Uncertainty: Reliable Representation Learning with Structural Constraints | arXiv:2601.16174v1 Announce Type: cross Abstract: Uncertainty estimation in machine learning has traditionally focused on the prediction stage, aiming to quantify confidence in model outputs while treating learned representations as deterministic and reliable by default. In this work, we challenge this implicit assumpt... | https://arxiv.org/abs/2601.16174 | Academic Papers | svg |
a78008c1479f762180dbb89282a3b73ef10064582bcc3123ea2aa82a4fec6a37 | 2026-01-23T00:00:00-05:00 | A Rolling-Space Branch-and-Price Algorithm for the Multi-Compartment Vehicle Routing Problem with Multiple Time Windows | arXiv:2601.16194v1 Announce Type: cross Abstract: This paper investigates the multi-compartment vehicle routing problem with multiple time windows (MCVRPMTW), an extension of the classical vehicle routing problem with time windows that considers vehicles equipped with multiple compartments and customers requiring servi... | https://arxiv.org/abs/2601.16194 | Academic Papers | svg |
1157d4a5ee376233c802874395381f28c624cf616f46ff160ed4e68c6d433c0c | 2026-01-23T00:00:00-05:00 | Representation-Driven Reinforcement Learning | arXiv:2305.19922v3 Announce Type: replace Abstract: We present a representation-driven framework for reinforcement learning. By representing policies as estimates of their expected values, we leverage techniques from contextual bandits to guide exploration and exploitation. Particularly, embedding a policy network into... | https://arxiv.org/abs/2305.19922 | Academic Papers | svg |
734e032083ffa4c80220d69d9c4b97ce4d578d4f9bf074509492b02a893ab78a | 2026-01-23T00:00:00-05:00 | Multi-event Video-Text Retrieval | arXiv:2308.11551v3 Announce Type: replace Abstract: Video-Text Retrieval (VTR) is a crucial multi-modal task in an era of massive video-text data on the Internet. A plethora of work characterized by using a two-stream Vision-Language model architecture that learns a joint representation of video-text pairs has become a... | https://arxiv.org/abs/2308.11551 | Academic Papers | svg |
9ddc1b7d28ac592382d488476164cd1a0bb49e4b89734833bea2a21acff5398d | 2026-01-23T00:00:00-05:00 | Strategic forecasting of internet of things technologies through patent social network and innovation cluster analysis | arXiv:2309.00707v2 Announce Type: replace Abstract: The rapid proliferation of Internet of Things (IoT) technologies necessitates robust forecasting mechanisms to guide strategic decision-making amid increasingly complex innovation landscapes. Despite extensive research employing patent analysis for technology forecast... | https://arxiv.org/abs/2309.00707 | Academic Papers | svg |
a9d29c0998a2b06970c0f4fe230dffbcfd4c344d84a6fb9e06fa7575ea6fa228 | 2026-01-23T00:00:00-05:00 | Multi-Layered Reasoning from a Single Viewpoint for Learning See-Through Grasping | arXiv:2312.09822v5 Announce Type: replace Abstract: Sensory substitution enables biological systems to perceive stimuli that are typically perceived by another organ, which is inspirational for physical agents. Multimodal perception of intrinsic and extrinsic interactions is critical in building an intelligent robot th... | https://arxiv.org/abs/2312.09822 | Academic Papers | svg |
437754f16013fb46f56d744b76ea7df1fc97e758e9025aff74fd34c902d3a8df | 2026-01-23T00:00:00-05:00 | Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages | arXiv:2401.18034v3 Announce Type: replace Abstract: Multilingual large language models (LLMs) are expensive to pretrain and often suffer from imbalances across languages and datasets, English-centric bias, tokenizer oversegmentation for morphologically rich low-resource languages, and the curse of multilinguality. We i... | https://arxiv.org/abs/2401.18034 | Academic Papers | svg |
8b85e5cd36ba8150b76d6e7c15dbec852d473d32b5ca5d271d0805fda083975d | 2026-01-23T00:00:00-05:00 | Scalable Multi-view Clustering via Explicit Kernel Features Maps | arXiv:2402.04794v2 Announce Type: replace Abstract: The proliferation of high-dimensional data from sources such as social media, sensor networks, and online platforms has created new challenges for clustering algorithms. Multi-view clustering, which integrates complementary information from multiple data perspectives,... | https://arxiv.org/abs/2402.04794 | Academic Papers | svg |
33922f707b247829487e0793f5d9427e5d92573313ffbbdb580caab111b78c36 | 2026-01-23T00:00:00-05:00 | Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes | arXiv:2402.05406v4 Announce Type: replace Abstract: Structured pruning is a promising approach to create smaller, faster large language models. However, existing methods typically rely on computing the gradient via backward passes, which can inflate memory requirements and compute costs. In this work we introduce Bonsa... | https://arxiv.org/abs/2402.05406 | Academic Papers | svg |
b8556d0e0dcfeb696ac08dcfc61b6705fc75381f255e7a2829aef2753ae857fb | 2026-01-23T00:00:00-05:00 | Thought of Search: Planning with Language Models Through The Lens of Efficiency | arXiv:2404.11833v3 Announce Type: replace Abstract: Among the most important properties of algorithms investigated in computer science are soundness, completeness, and complexity. These properties, however, are rarely analyzed for the vast collection of recently proposed methods for planning with large language models.... | https://arxiv.org/abs/2404.11833 | Academic Papers | svg |
e3b17e8f61001b95c891222c4d79508222c37469b1891c1406f034ec4027f1bd | 2026-01-23T00:00:00-05:00 | Sign Language-Based versus Touch-Based Input for Deaf Users with Interactive Personal Assistants in Simulated Kitchen Environments | arXiv:2404.14610v2 Announce Type: replace Abstract: In this study, we assess the usability of interactive personal assistants (IPAs), such as Amazon Alexa, in a simulated kitchen smart home environment, with deaf and hard of hearing users. Participants engage in activities in a way that causes their hands to get dirty.... | https://arxiv.org/abs/2404.14610 | Academic Papers | svg |
070103bf51ea97c09c87dc1605b0cfb2a5083dc511dbf7769be7126872671922 | 2026-01-23T00:00:00-05:00 | Efficient Multimodal Large Language Models: A Survey | arXiv:2405.10739v3 Announce Type: replace Abstract: In the past year, Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering, visual understanding and reasoning. However, the extensive model size and high training and inference costs have hindered th... | https://arxiv.org/abs/2405.10739 | Academic Papers | svg |
74f6bde368992d4ecd7434ca77242552b0801a8fca5b1d410e9cf0b05e9a3445 | 2026-01-23T00:00:00-05:00 | Neural Green's Operators for Parametric Partial Differential Equations | arXiv:2406.01857v5 Announce Type: replace Abstract: This work introduces a paradigm for constructing parametric neural operators that are derived from finite-dimensional representations of Green's operators for linear partial differential equations (PDEs). We refer to such neural operators as Neural Green's Operators (... | https://arxiv.org/abs/2406.01857 | Academic Papers | svg |
3d8e001eae0855159554377276acf9c5660641fc6bd7ba6e1a080f85e906486b | 2026-01-23T00:00:00-05:00 | A Comprehensive Study on Large Language Models for Mutation Testing | arXiv:2406.09843v5 Announce Type: replace Abstract: Large Language Models (LLMs) have recently been used to generate mutants in both research work and in industrial practice. However, there has been no comprehensive empirical study of their performance for this increasingly important LLM-based Software Engineering appl... | https://arxiv.org/abs/2406.09843 | Academic Papers | svg |
30866ef5e331d0f4a924bbbebf17a04d0f24e231ecab742ed8ae45473ac29742 | 2026-01-23T00:00:00-05:00 | On the Exponential Convergence for Offline RLHF with Pairwise Comparisons | arXiv:2406.12205v2 Announce Type: replace Abstract: We consider the problem of offline reinforcement learning from human feedback (RLHF) with pairwise comparisons proposed by Zhu et al. (2023), where the implicit reward is a linear function of an unknown parameter. Given an offline dataset, our objective consists in as... | https://arxiv.org/abs/2406.12205 | Academic Papers | svg |
5beca48cac402794f56564287d404b95d0bfcf5e6ffe7779f895fd5dd7d519fd | 2026-01-23T00:00:00-05:00 | Vision-Language Models Align with Human Neural Representations in Concept Processing | arXiv:2407.17914v3 Announce Type: replace Abstract: Recent studies suggest that transformer-based vision-language models (VLMs) capture the multimodality of concept processing in the human brain. However, a systematic evaluation exploring different types of VLM architectures and the role played by visual and textual co... | https://arxiv.org/abs/2407.17914 | Academic Papers | svg |
c2d22d7d15776120779f2b3c6f9741c9e165a24ed3bc1ca18dd2a88b3092abe1 | 2026-01-23T00:00:00-05:00 | 120 Domain-Specific Languages for Security | arXiv:2408.06219v3 Announce Type: replace Abstract: Security engineering, from security requirements engineering to the implementation of cryptographic protocols, is often supported by domain-specific languages (DSLs). Unfortunately, a lack of knowledge about these DSLs, such as which security aspects are addressed and... | https://arxiv.org/abs/2408.06219 | Academic Papers | svg |
7e2fe5040fbcfa2d338c293ca918f3524d7cd3f7579ef57b882c93a43e5ab22b | 2026-01-23T00:00:00-05:00 | Reinforcement Learning Compensated Model Predictive Control for Off-road Driving on Unknown Deformable Terrain | arXiv:2408.09253v2 Announce Type: replace Abstract: This study presents an Actor-Critic reinforcement learning Compensated Model Predictive Controller (AC2MPC) designed for high-speed, off-road autonomous driving on deformable terrains. Addressing the difficulty of modeling unknown tire-terrain interaction and ensuring... | https://arxiv.org/abs/2408.09253 | Academic Papers | svg |
ddc6216d88c1e1eedfaffc28568d6e68206e5420f3ec289677161e03403d1fa5 | 2026-01-23T00:00:00-05:00 | Medal Matters: Probing LLMs' Failure Cases Through Olympic Rankings | arXiv:2409.06518v3 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable success in natural language processing tasks, yet their internal knowledge structures remain poorly understood. This study examines these structures through the lens of historical Olympic medal tallies, evaluating ... | https://arxiv.org/abs/2409.06518 | Academic Papers | svg |
c6d3db36884c41a89201aea2ec8b08a60bb8ad57e913ab289857cd9c1e6c63b4 | 2026-01-23T00:00:00-05:00 | How hard can it be? Quantifying MITRE attack campaigns with attack trees and cATM logic | arXiv:2410.06692v4 Announce Type: replace Abstract: The landscape of cyber threats grows more complex by the day. Advanced Persistent Threats carry out attack campaigns - e.g. operations Dream Job, Wocao, and WannaCry - against which cybersecurity practitioners must defend. To prioritise which of these to defend agains... | https://arxiv.org/abs/2410.06692 | Academic Papers | svg |
be494436c3dc3d47d2f9fda286f760babc5e80c5cf032980bdd535b23c5070b9 | 2026-01-23T00:00:00-05:00 | CropCraft: Complete Structural Characterization of Crop Plants From Images | arXiv:2411.09693v2 Announce Type: replace Abstract: The ability to automatically build 3D digital twins of plants from images has countless applications in agriculture, environmental science, robotics, and other fields. However, current 3D reconstruction methods fail to recover complete shapes of plants due to heavy oc... | https://arxiv.org/abs/2411.09693 | Academic Papers | svg |
8b0575878067d9546d835fdef03e5895c95eeaa18dccfd6028f06913e059f1be | 2026-01-23T00:00:00-05:00 | Robust Output Tracking for Induced Seismicity Mitigation in Underground Reservoirs Governed by a Nonlinear 3D PDE-ODE System | arXiv:2412.06327v3 Announce Type: replace Abstract: This paper presents a robust output-feedback controller for induced seismicity mitigation in geological reservoirs described by a coupled 3D PDE-ODE model. The controller is a MIMO Super-Twisting design, producing a continuous control signal and requiring minimal mode... | https://arxiv.org/abs/2412.06327 | Academic Papers | svg |
ef416410e68f31f3d8939222c4234eb1c504a58ef2a2c0d8bd77f0de513ef5fc | 2026-01-23T00:00:00-05:00 | FREYJA: Efficient Join Discovery in Data Lakes | arXiv:2412.06637v2 Announce Type: replace Abstract: Data lakes are massive repositories of raw and heterogeneous data, designed to meet the requirements of modern data storage. Nonetheless, this same philosophy increases the complexity of performing discovery tasks to find relevant data for subsequent processing. As a ... | https://arxiv.org/abs/2412.06637 | Academic Papers | svg |
8b4c36ebb2f292671240a8791022964e352cef5a35b6c7a53d04a85f54ab3eb0 | 2026-01-23T00:00:00-05:00 | Unexpected but informative: What fixation-related potentials tell us about the processing of confusing program code | arXiv:2412.10099v3 Announce Type: replace Abstract: As software pervades more and more areas of our professional and personal lives, there is an ever-increasing need to maintain software and for programmers to efficiently write and understand program code. In the first study of its kind, we analyze fixation-related pot... | https://arxiv.org/abs/2412.10099 | Academic Papers | svg |
c5289f7fc473dd676b5d1047540d5b779181abb622661de29758dff42a155ed6 | 2026-01-23T00:00:00-05:00 | ViSymRe: Vision-guided Multimodal Symbolic Regression | arXiv:2412.11139v3 Announce Type: replace Abstract: Extracting simple mathematical expression from an observational dataset to describe complex natural phenomena is one of the core objectives of artificial intelligence (AI). This field is known as symbolic regression (SR). Traditional SR models are based on genetic pro... | https://arxiv.org/abs/2412.11139 | Academic Papers | svg |
984789daa37786fbe2922c8a2751793fda4cb383a50835c15fac0d7c4a7ab5ea | 2026-01-23T00:00:00-05:00 | Language-guided Medical Image Segmentation with Target-informed Multi-level Contrastive Alignments | arXiv:2412.13533v3 Announce Type: replace Abstract: Medical image segmentation is a fundamental task in numerous medical engineering applications. Recently, language-guided segmentation has shown promise in medical scenarios where textual clinical reports are readily available as semantic guidance. Clinical reports con... | https://arxiv.org/abs/2412.13533 | Academic Papers | svg |
5ae8c0ae5f189a2e38c1efc93d52878704516d6ebccc078e9884f402afae5909 | 2026-01-23T00:00:00-05:00 | Data-driven tool wear prediction in milling, based on a process-integrated single-sensor approach | arXiv:2412.19950v5 Announce Type: replace Abstract: Accurate tool wear prediction is essential for maintaining productivity and minimizing costs in machining. However, the complex nature of the tool wear process poses significant challenges to achieving reliable predictions. This study explores data-driven methods, in ... | https://arxiv.org/abs/2412.19950 | Academic Papers | svg |
48cb1fba6ff031e79cfcb82a6f3c4e27bf3df5576d1050461f884e8f7849c8d8 | 2026-01-23T00:00:00-05:00 | Explaining k-Nearest Neighbors: Abductive and Counterfactual Explanations | arXiv:2501.06078v2 Announce Type: replace Abstract: Despite the wide use of $k$-Nearest Neighbors as classification models, their explainability properties remain poorly understood from a theoretical perspective. While nearest neighbors classifiers offer interpretability from a ``data perspective'', in which the classi... | https://arxiv.org/abs/2501.06078 | Academic Papers | svg |
a8eae12501297908e493d1bf6ec8f1035b4cfec3fb1d9b314df5103a8bef2b2f | 2026-01-23T00:00:00-05:00 | A domain decomposition strategy for natural imposition of mixed boundary conditions in port-Hamiltonian systems | arXiv:2501.06107v4 Announce Type: replace Abstract: In this contribution, a finite element scheme to impose mixed boundary conditions without introducing Lagrange multipliers is presented for hyperbolic systems described as port-Hamiltonian systems. The strategy relies on finite element exterior calculus and domain dec... | https://arxiv.org/abs/2501.06107 | Academic Papers | svg |
27304fd438d17f1df1a0193b6c999edfa8cb3d77e69e8907b2b1258650a19bf7 | 2026-01-23T00:00:00-05:00 | NP-Hard Lower Bound Complexity for Semantic Self-Verification | arXiv:2501.15446v2 Announce Type: replace Abstract: We model Semantic Self-Verification (SSV) as the problem of determining whether a statement accurately characterizes its own semantic properties within a given interpretive framework that formalizes a challenge in AI safety and fairness: can an AI system verify that i... | https://arxiv.org/abs/2501.15446 | Academic Papers | svg |
d9d337d75bfe2d2788471f585d4b7d83be8bf1e0b7253546eb32046c0abf6aa2 | 2026-01-23T00:00:00-05:00 | Information-theoretic Distinctions Between Deception and Confusion | arXiv:2501.16448v2 Announce Type: replace Abstract: We propose an information-theoretic formalization of the distinction between two fundamental AI safety failure modes: deceptive alignment and goal drift. While both can lead to systems that appear misaligned, we demonstrate that they represent distinct forms of inform... | https://arxiv.org/abs/2501.16448 | Academic Papers | svg |
d971e8b307f8d90bcc2b3ca2e686e7c3037fc8d44fd97c1d700b7001fd2c22c9 | 2026-01-23T00:00:00-05:00 | UniAttn: Reducing Inference Costs via Softmax Unification for Post-Training LLMs | arXiv:2502.00439v2 Announce Type: replace Abstract: Post-training is essential for adapting Large Language Models (LLMs) to real-world applications. Deploying post-trained models faces significant challenges due to substantial memory overhead and noticeable inference latency. Existing work has identified significant re... | https://arxiv.org/abs/2502.00439 | Academic Papers | svg |
7da6edde89270fbe42ca3df9b20a0bb67ad9d01f0a6da95246838d2b642cac91 | 2026-01-23T00:00:00-05:00 | Sparse Data Diffusion for Scientific Simulations in Biology and Physics | arXiv:2502.02448v3 Announce Type: replace Abstract: Sparse data is fundamental to scientific simulations in biology and physics, from single-cell gene expression to particle calorimetry, where exact zeros encode physical absence rather than weak signal. However, existing diffusion models lack the physical rigor to fait... | https://arxiv.org/abs/2502.02448 | Academic Papers | svg |
d4def3398230cf253b9cc9fd4ee4e37c8de7ac65ee6edc238ca834899b46c7a3 | 2026-01-23T00:00:00-05:00 | A Match Made in Heaven? AI-driven Matching of Vulnerabilities and Security Unit Tests | arXiv:2502.03365v4 Announce Type: replace Abstract: Software vulnerabilities are often detected via taint analysis, penetration testing, or fuzzing. They are also found via unit tests that exercise security-sensitive behavior with specific inputs, called vulnerability-witnessing tests. Generative AI models could help d... | https://arxiv.org/abs/2502.03365 | Academic Papers | svg |
1750a92d067b002e6f622dd245ff499ecc92348b73e01c3ea85fc561da17d580 | 2026-01-23T00:00:00-05:00 | Cognitive AI framework 2.0: advances in the simulation of human thought | arXiv:2502.04259v2 Announce Type: replace Abstract: The Human Cognitive Simulation Framework proposes a governed cognitive AI architecture designed to improve personalization, adaptability, and long-term coherence in human AI interaction. The framework integrates short-term memory (conversation context), long-term memo... | https://arxiv.org/abs/2502.04259 | Academic Papers | svg |
b3d74753bbc24cb6abf056e28a1504209acde6a89838a81a0936962ea81b67ba | 2026-01-23T00:00:00-05:00 | "I never would have thought to say this": Example-Based Exploration to Balance Scientists' Writing Preferences with Public Science Communication Strategies | arXiv:2502.05287v3 Announce Type: replace Abstract: Public-facing science communication is important in garnering interest, engagement, and trust in science. Social media platforms provide scientists with opportunities to reach broader audiences, yet many resist adopting social media writing strategies because the stra... | https://arxiv.org/abs/2502.05287 | Academic Papers | svg |
11b9ea8f78ff70f54fca664d653eed9cb571eba0e2c89032180822ec8b8ae050 | 2026-01-23T00:00:00-05:00 | GENERator: A Long-Context Generative Genomic Foundation Model | arXiv:2502.07272v4 Announce Type: replace Abstract: The rapid advancement of DNA sequencing has produced vast genomic datasets, yet interpreting and engineering genomic function remain fundamental challenges. Recent large language models have opened new avenues for genomic analysis, but existing approaches are often li... | https://arxiv.org/abs/2502.07272 | Academic Papers | svg |
c2999198a3cf3b558e801005e90b27aeb7abf8bcf634d379f94d65a26db3ebc4 | 2026-01-23T00:00:00-05:00 | SCALAR: Scientific Citation-based Live Assessment of Long-context Academic Reasoning | arXiv:2502.13753v2 Announce Type: replace Abstract: Long-context understanding has emerged as a critical capability for large language models (LLMs). However, evaluating this ability remains challenging. We present SCALAR, a benchmark designed to assess citation-grounded long-context reasoning in academic writing. SCAL... | https://arxiv.org/abs/2502.13753 | Academic Papers | svg |
e83367e184df3a7658b523faa2fbdf6cbeae8fdd8bac2ce85252acfc1caab46d | 2026-01-23T00:00:00-05:00 | I-MCTS: Enhancing Agentic AutoML via Introspective Monte Carlo Tree Search | arXiv:2502.14693v4 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have shown remarkable potential in automating machine learning tasks. However, existing LLM-based agents often struggle with low-diversity and suboptimal code generation. While recent work has introduced Monte Carlo ... | https://arxiv.org/abs/2502.14693 | Academic Papers | svg |
8f80a8a1398ec9a48ca73427cfbe0db403fc99fe0e42ddaa5bbdb6ae1f218585 | 2026-01-23T00:00:00-05:00 | English K_Quantization of LLMs Does Not Disproportionately Diminish Multilingual Performance | arXiv:2503.03592v4 Announce Type: replace Abstract: For consumer usage of locally deployed LLMs, the GGUF format and k\_quantization are invaluable tools for maintaining the performance of the original model while reducing it to sizes deployable with consumer-grade hardware. The number of bits dedicated to each weight ... | https://arxiv.org/abs/2503.03592 | Academic Papers | svg |
43daf0d190cf0f4b9a7dd3891037b55ec47e430e2c85901ade535ce9fcf51fe5 | 2026-01-23T00:00:00-05:00 | Games with $\omega$-Automatic Preference Relations | arXiv:2503.04759v3 Announce Type: replace Abstract: This paper investigates Nash equilibria (NEs) in multi-player turn-based games on graphs, where player preferences are modeled as $\omega$-automatic relations via deterministic parity automata. Unlike much of the existing literature, which focuses on specific reward f... | https://arxiv.org/abs/2503.04759 | Academic Papers | svg |
cb96875ec432f2d00eb5065930d9c4cd3fc00e4ff30fe7e18bccc3a2c80b2439 | 2026-01-23T00:00:00-05:00 | Decoding Safety Feedback from Diverse Raters: A Data-driven Lens on Responsiveness to Severity | arXiv:2503.05609v5 Announce Type: replace Abstract: Ensuring the safety of Generative AI requires a nuanced understanding of pluralistic viewpoints. In this paper, we introduce a novel data-driven approach for analyzing ordinal safety ratings in pluralistic settings. Specifically, we address the challenge of interpreti... | https://arxiv.org/abs/2503.05609 | Academic Papers | svg |
c1465b67c7ece4e99b793a84cd2a8bef84e070a10bce0b384fced3dc197796ae | 2026-01-23T00:00:00-05:00 | MedSimAI: Simulation and Formative Feedback Generation to Enhance Deliberate Practice in Medical Education | arXiv:2503.05793v2 Announce Type: replace Abstract: Medical education faces challenges in providing scalable, consistent clinical skills training. Simulation with standardized patients (SPs) develops communication and diagnostic skills but remains resource-intensive and variable in feedback quality. Existing AI-based t... | https://arxiv.org/abs/2503.05793 | Academic Papers | svg |
d87bd6cf75599be1713d25d1ff09d9ea67cd524ea86eac3b56f2c1803c363cf7 | 2026-01-23T00:00:00-05:00 | GRITHopper: Decomposition-Free Multi-Hop Dense Retrieval | arXiv:2503.07519v2 Announce Type: replace Abstract: Decomposition-based multi-hop retrieval methods rely on many autoregressive steps to break down complex queries, which breaks end-to-end differentiability and is computationally expensive. Decomposition-free methods tackle this, but current decomposition-free approach... | https://arxiv.org/abs/2503.07519 | Academic Papers | svg |
230bd79f8da7dc374bd0765e51436e49f48597effc6e1e9fa18776e5b7a02605 | 2026-01-23T00:00:00-05:00 | Chat-TS: Enhancing Multi-Modal Reasoning Over Time-Series and Natural Language Data | arXiv:2503.10883v2 Announce Type: replace Abstract: Large language models are being rapidly deployed across many fields such as healthcare, finance, transportation, and energy, where time-series data are fundamental components. The current works are still limited in their ability to perform reasoning that involves both... | https://arxiv.org/abs/2503.10883 | Academic Papers | svg |
de5642fe1372be608870d55386525394ae80334efba4fc989e9bb6d4e5f1dddd | 2026-01-23T00:00:00-05:00 | Variational Bayesian Personalized Ranking | arXiv:2503.11067v2 Announce Type: replace Abstract: Pairwise learning underpins implicit collaborative filtering, yet its effectiveness is often hindered by sparse supervision, noisy interactions, and popularity-driven exposure bias. In this paper, we propose Variational Bayesian Personalized Ranking (VarBPR), a tracta... | https://arxiv.org/abs/2503.11067 | Academic Papers | svg |
7fffed33b880e26c0766d80f5cbf7c7978c2004066f68b866718eb825c6ba9ba | 2026-01-23T00:00:00-05:00 | Simulating Dual-Pixel Images From Ray Tracing For Depth Estimation | arXiv:2503.11213v2 Announce Type: replace Abstract: Many studies utilize dual-pixel (DP) sensor phase characteristics for various applications, such as depth estimation and deblurring. However, since the DP image features are entirely determined by the camera hardware, DP-depth paired datasets are very scarce, especial... | https://arxiv.org/abs/2503.11213 | Academic Papers | svg |
63030e10ca82eb8ea65d5c70d241eac07d47a4e41da79ebe57949cc3102d1ac5 | 2026-01-23T00:00:00-05:00 | A Peek Behind the Curtain: Using Step-Around Prompt Engineering to Identify Bias and Misinformation in GenAI Models | arXiv:2503.15205v2 Announce Type: replace Abstract: This research examines the emerging technique of step-around prompt engineering in GenAI research, a method that deliberately bypasses AI safety measures to expose underlying biases and vulnerabilities in GenAI models. We discuss how Internet-sourced training data int... | https://arxiv.org/abs/2503.15205 | Academic Papers | svg |
4319c208cf14eabf3600635ac6feb7746c03e457c7816fb393d2599660840cc1 | 2026-01-23T00:00:00-05:00 | ImputeGAP: A Comprehensive Library for Time Series Imputation | arXiv:2503.15250v2 Announce Type: replace Abstract: With the prevalence of sensor failures, imputation, the process of estimating missing values, has emerged as the cornerstone of time series data pre-processing. While numerous imputation algorithms have been developed to repair these data gaps, existing time series li... | https://arxiv.org/abs/2503.15250 | Academic Papers | svg |
d26f8290e1adc0267e4a81e7a024f10a30552e12ac33bad708601c32475ca797 | 2026-01-23T00:00:00-05:00 | Trees in Coalgebra from Generalized Reachability | arXiv:2503.15585v4 Announce Type: replace Abstract: An automaton is called reachable if every state is reachable from the initial state. This notion has been generalized coalgebraically in two ways: first, via a universal property on pointed coalgebras, namely, that a reachable coalgebra has no proper subcoalgebras; an... | https://arxiv.org/abs/2503.15585 | Academic Papers | svg |
5616caa55706e23bf74cd47c944d2d96df0f791ec4afd7606000d23ae260ee52 | 2026-01-23T00:00:00-05:00 | Poor Alignment and Steerability of Large Language Models: Evidence from College Admission Essays | arXiv:2503.20062v2 Announce Type: replace Abstract: People are increasingly using technologies equipped with large language models (LLM) to write texts for formal communication, which raises two important questions at the intersection of technology and society: Who do LLMs write like (model alignment); and can LLMs be ... | https://arxiv.org/abs/2503.20062 | Academic Papers | svg |
19bb1afc3dbcc9f1d94ad6fa8e8dd8ff7dedaf507536834fff42322646101bea | 2026-01-23T00:00:00-05:00 | Is Your Writing Being Mimicked by AI? Unveiling Imitation with Invisible Watermarks in Creative Writing | arXiv:2504.00035v3 Announce Type: replace Abstract: Efficient knowledge injection methods for Large Language Models (LLMs), such as In-Context Learning, knowledge editing, and efficient parameter fine-tuning, significantly enhance model utility on downstream tasks. However, they also pose substantial risks of unauthori... | https://arxiv.org/abs/2504.00035 | Academic Papers | svg |
3f5a3465ac6947a30a52342beeca34bee591c517da0382b3487736c92e8f0deb | 2026-01-23T00:00:00-05:00 | On shallow feedforward neural networks with inputs from a topological space | arXiv:2504.02321v2 Announce Type: replace Abstract: We study feedforward neural networks with inputs from a topological space (TFNNs). We prove a universal approximation theorem for shallow TFNNs, which demonstrates their capacity to approximate any continuous function defined on this topological space. As an applicati... | https://arxiv.org/abs/2504.02321 | Academic Papers | svg |
d4fa470b60c10ad579df6de5dadf11914a8dbe4b2b7569fb312ca1d0ab478289 | 2026-01-23T00:00:00-05:00 | A Scalable Predictive Modelling Approach to Identifying Duplicate Adverse Event Reports for Drugs and Vaccines | arXiv:2504.03729v2 Announce Type: replace Abstract: Objectives: To advance state-of-the-art for duplicate detection in large-scale pharmacovigilance databases and achieve more consistent performance across adverse event reports from different countries. Background: Unlinked adverse event reports referring to the same c... | https://arxiv.org/abs/2504.03729 | Academic Papers | svg |
90629c74f9cbdf888588785428d37f9f4ba8b2e21bfbf827488f2be08b06519d | 2026-01-23T00:00:00-05:00 | Embracing Ambiguity: Bayesian Nonparametrics and Stakeholder Participation for Ambiguity-Aware Safety Evaluation | arXiv:2504.15211v2 Announce Type: replace Abstract: Evaluations of generative AI models often collapse nuanced behaviour into a single number computed for a single decoding configuration. Such point estimates obscure tail risks, demographic disparities, and the existence of multiple near-optimal operating points. We pr... | https://arxiv.org/abs/2504.15211 | Academic Papers | svg |
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