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954c3dd7411e47a5aa232c2976bf5857eefa514d2c8aefecb1c4fde1a0956dda | 2026-01-16T00:00:00-05:00 | On some Exotic Cylindrical Algebraic Decompositions and Cells | arXiv:2601.09795v1 Announce Type: cross Abstract: Cylindrical Algebraic Decompositions (CADs) endowed with additional topological properties have found applications beyond their original logical setting, including algorithmic optimizations in CAD construction, robot motion planning, and the algorithmic study of the top... | https://arxiv.org/abs/2601.09795 | Academic Papers | svg |
613243d0dc7346cd80196dc4d1cf5e388a2183e244cf50a7d49be7119bd4f48e | 2026-01-16T00:00:00-05:00 | Shallow-KAN Based Solution of Moving Boundary PDEs | arXiv:2601.09818v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) require significantly smaller architectures compared to multilayer perceptron (MLP)-based approaches, while retaining expressive power through spline-based activations. We propose a shallow KAN framework that directly approximates the t... | https://arxiv.org/abs/2601.09818 | Academic Papers | svg |
7adab6df2c3593ab630840fb66744544d9939ae7b70d953771b4ce3795ad7a55 | 2026-01-16T00:00:00-05:00 | Accelerated Regularized Wasserstein Proximal Sampling Algorithms | arXiv:2601.09848v1 Announce Type: cross Abstract: We consider sampling from a Gibbs distribution by evolving a finite number of particles using a particular score estimator rather than Brownian motion. To accelerate the particles, we consider a second-order score-based ODE, similar to Nesterov acceleration. In contrast... | https://arxiv.org/abs/2601.09848 | Academic Papers | svg |
0995ca14942b9d9c7f6bf805a1234b3b82c10a4962b7f06440888415245df9c8 | 2026-01-16T00:00:00-05:00 | Distortion maps for elliptic curves over finite fields | arXiv:2601.09904v1 Announce Type: cross Abstract: The Weil pairing on elliptic curves has deep links with discrete logarithm problems. In practice, to better suit the functionalities of cryptosystems, one often needs to modify the original Weil pairing via what is called a distortion map. We propose a study on the ques... | https://arxiv.org/abs/2601.09904 | Academic Papers | svg |
49d78f6ba1dca46528659ea268c6f51919be1fbad46852354a39ce3ef0c8f162 | 2026-01-16T00:00:00-05:00 | Learning to Decode in Parallel: Self-Coordinating Neural Network for Real-Time Quantum Error Correction | arXiv:2601.09921v1 Announce Type: cross Abstract: Fast, reliable decoders are pivotal components for enabling fault-tolerant quantum computation (FTQC). Neural network decoders like AlphaQubit have demonstrated potential, achieving higher accuracy than traditional human-designed decoding algorithms. However, existing i... | https://arxiv.org/abs/2601.09921 | Academic Papers | svg |
e159e97f47e77cf6da42dae0738728278ef5159f0a550814ab369a8895c4e396 | 2026-01-16T00:00:00-05:00 | A Level Set Method on Particle Flow Maps | arXiv:2601.09939v1 Announce Type: cross Abstract: This paper introduces a Particle Flow Map Level Set (PFM-LS) method for high-fidelity interface tracking. We store level-set values, gradients, and Hessians on particles concentrated in a narrow band around the interface, advecting them via bidirectional flow maps while... | https://arxiv.org/abs/2601.09939 | Academic Papers | svg |
6f673ef5b55ae2250d3fce564f70ddf99deec0b69cf0a41aa9961c1b2466bb7c | 2026-01-16T00:00:00-05:00 | Interfacing Superconductor and Semiconductor Digital Electronics | arXiv:2601.09969v1 Announce Type: cross Abstract: Interface circuits are the key components that enable the hybrid integration of superconductor and semiconductor digital electronics. The design requirements of superconductor-semiconductor interface circuits vary depending on the application, such as high-performance c... | https://arxiv.org/abs/2601.09969 | Academic Papers | svg |
abe5a04bff58978128ec653b7eb63f59814fcd6aaea1734d4844b0f14e634202 | 2026-01-16T00:00:00-05:00 | Performance of AI agents based on reasoning language models on ALD process optimization tasks | arXiv:2601.09980v1 Announce Type: cross Abstract: In this work we explore the performance and behavior of reasoning large language models to autonomously optimize atomic layer deposition (ALD) processes. In the ALD process optimization task, an agent built on top of a reasoning LLM has to find optimal dose times for an... | https://arxiv.org/abs/2601.09980 | Academic Papers | svg |
8868ad60a15cc6aebfb5159d66aef8f7c6bf24b2476786040558ac8cdf343a64 | 2026-01-16T00:00:00-05:00 | Clustering-Based User Selection in Federated Learning: Metadata Exploitation for 3GPP Networks | arXiv:2601.10013v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative model training without sharing raw user data, but conventional simulations often rely on unrealistic data partitioning and current user selection methods ignore data correlation among users. To address these challenges, this... | https://arxiv.org/abs/2601.10013 | Academic Papers | svg |
008e0ef6c15a7245308420d1e0e2b35dfe79f3f415c2be5acc672012de23fe6c | 2026-01-16T00:00:00-05:00 | What Understanding Means in AI-Laden Astronomy | arXiv:2601.10038v1 Announce Type: cross Abstract: Artificial intelligence is rapidly transforming astronomical research, yet the scientific community has largely treated this transformation as an engineering challenge rather than an epistemological one. This perspective article argues that philosophy of science offers ... | https://arxiv.org/abs/2601.10038 | Academic Papers | svg |
122b2e98625f2b209a0d85d6ec47993694e991fb732a5af524c2402c972c009a | 2026-01-16T00:00:00-05:00 | Instruction Finetuning LLaMA-3-8B Model Using LoRA for Financial Named Entity Recognition | arXiv:2601.10043v1 Announce Type: cross Abstract: Particularly, financial named-entity recognition (NER) is one of the many important approaches to translate unformatted reports and news into structured knowledge graphs. However, free, easy-to-use large language models (LLMs) often fail to differentiate organisations a... | https://arxiv.org/abs/2601.10043 | Academic Papers | svg |
463b197b96f1cfd85c33a605fa2e9b7fe77354dfec9e2d94665c809f05fe6410 | 2026-01-16T00:00:00-05:00 | Nearest Kronecker Product Decomposition Based Subband Adaptive Filter: Algorithms and Applications | arXiv:2601.10078v1 Announce Type: cross Abstract: Recently, the nearest Kronecker product (NKP) decomposition-based normalized least mean square (NLMS-NKP) algorithm has demonstrated superior convergence performance compared to the conventional NLMS algorithm. However, its convergence rate exhibits significant degradat... | https://arxiv.org/abs/2601.10078 | Academic Papers | svg |
0d86264abf026775cf112feb3ee043abec43d2cc6c3868ea52e7669a5dc5b64c | 2026-01-16T00:00:00-05:00 | Bayesian Model Selection for Complex Flows of Yield Stress Fluids | arXiv:2601.10115v1 Announce Type: cross Abstract: Modeling yield stress fluids in complex flow scenarios presents significant challenges, particularly because conventional rheological characterization methods often yield material parameters that are not fully representative of the intricate constitutive behavior observ... | https://arxiv.org/abs/2601.10115 | Academic Papers | svg |
918da3a3ed195386d101fa347783be5ac6da2f5985db48b4bbbe9f337e22e9d1 | 2026-01-16T00:00:00-05:00 | A volume penalization method for solving conjugate scalar transport with interfacial jump conditions | arXiv:2601.10134v1 Announce Type: cross Abstract: Conjugate scalar transport with interfacial jump conditions on complex interfacial geometries is common in thermal and chemical processes, while its accurate and efficient simulations are still quite challenging. In the present study, a novel treatment of a two-phase in... | https://arxiv.org/abs/2601.10134 | Academic Papers | svg |
1748eb7ec8411a25b5e1c429d4c2e4b68b079441affb0fbecc2390f68f30d5d0 | 2026-01-16T00:00:00-05:00 | On 3-Connected Planar Graphs with Unique Orientable Circuit Double Covers | arXiv:2601.10171v1 Announce Type: cross Abstract: A circuit double cover of a bridgeless graph is a collection of even subgraphs such that every edge is contained in exactly two subgraphs of the given collection. Such a circuit double cover describes an embedding of the corresponding graph onto a surface. In this paper... | https://arxiv.org/abs/2601.10171 | Academic Papers | svg |
8a4457d38db0468877ddff1da7f250ae5ada670bb55d154511aab4c52238a8e6 | 2026-01-16T00:00:00-05:00 | Discrete versus continuous -- lattice models and their exact continuous counterparts | arXiv:2601.10184v1 Announce Type: cross Abstract: We review and study the correspondence between discrete lattice/chain models of interacting particles and their continuous counterparts represented by partial differential equations. We study the correspondence problem for nearest neighbour interaction lattice models as... | https://arxiv.org/abs/2601.10184 | Academic Papers | svg |
fa7f9149db30e3b77609a67f8f1dddebc6ac35ee4672da5b312f7eadc41314d9 | 2026-01-16T00:00:00-05:00 | Adversarial Hypothesis Testing for Quantum Channels | arXiv:2601.10243v1 Announce Type: cross Abstract: This paper presents a systematic study of adversarial hypothesis testing for both quantum-quantum (QQ) and classical-quantum (CQ) channels. Unlike conventional channel discrimination, we consider a framework where the sender, Alice, selects the channel input adversarial... | https://arxiv.org/abs/2601.10243 | Academic Papers | svg |
91e7252707f23b49fa247007e9f2fea3b20bcdea9ba7d2a243dae76142e1416b | 2026-01-16T00:00:00-05:00 | Cell Behavior Video Classification Challenge, a benchmark for computer vision methods in time-lapse microscopy | arXiv:2601.10250v1 Announce Type: cross Abstract: The classification of microscopy videos capturing complex cellular behaviors is crucial for understanding and quantifying the dynamics of biological processes over time. However, it remains a frontier in computer vision, requiring approaches that effectively model the s... | https://arxiv.org/abs/2601.10250 | Academic Papers | svg |
92293915edd70a75e4fe74f9d93aeecafdd282354d80e0fc015fd767414ff4be | 2026-01-16T00:00:00-05:00 | Sim2Real Deep Transfer for Per-Device CFO Calibration | arXiv:2601.10264v1 Announce Type: cross Abstract: Carrier Frequency Offset (CFO) estimation in Orthogonal Frequency Division Multiplexing (OFDM) systems faces significant performance degradation across heterogeneous software-defined radio (SDR) platforms due to uncalibrated hardware impairments. Existing deep neural ne... | https://arxiv.org/abs/2601.10264 | Academic Papers | svg |
2d08c19e28561c3fa93de6bcdae98849de7dea087d0268f4387771a7c701dc7a | 2026-01-16T00:00:00-05:00 | On gradient stability in nonlinear PDE models and inference in interacting particle systems | arXiv:2601.10326v1 Announce Type: cross Abstract: We consider general parameter to solution maps $\theta \mapsto \mathcal G(\theta)$ of non-linear partial differential equations and describe an approach based on a Banach space version of the implicit function theorem to verify the gradient stability condition of Nickl&... | https://arxiv.org/abs/2601.10326 | Academic Papers | svg |
96bbde4d4fcb23216db181319fb251a05e2998a7ba83bfe972519a67e3dee864 | 2026-01-16T00:00:00-05:00 | H-EFT-VA: An Effective-Field-Theory Variational Ansatz with Provable Barren Plateau Avoidance | arXiv:2601.10479v1 Announce Type: cross Abstract: Variational Quantum Algorithms (VQAs) are critically threatened by the Barren Plateau (BP) phenomenon. In this work, we introduce the H-EFT Variational Ansatz (H-EFT-VA), an architecture inspired by Effective Field Theory (EFT). By enforcing a hierarchical "UV-cutoff" o... | https://arxiv.org/abs/2601.10479 | Academic Papers | svg |
2693bc309986ab9316e962c5f171dc050bd1d7ff568e4ceeb47fc3fa68cb51e8 | 2026-01-16T00:00:00-05:00 | CROCS: A Two-Stage Clustering Framework for Behaviour-Centric Consumer Segmentation with Smart Meter Data | arXiv:2601.10494v1 Announce Type: cross Abstract: With grid operators confronting rising uncertainty from renewable integration and a broader push toward electrification, Demand-Side Management (DSM) -- particularly Demand Response (DR) -- has attracted significant attention as a cost-effective mechanism for balancing ... | https://arxiv.org/abs/2601.10494 | Academic Papers | svg |
b6cc58c9286a14f5e5eedf1606c837b1a9a491d429a3454c0f5f665f824d8bb6 | 2026-01-16T00:00:00-05:00 | The incompatibility of the Condorcet winner and loser criteria with positive involvement and resolvability | arXiv:2601.10506v1 Announce Type: cross Abstract: We prove that there is no preferential voting method satisfying the Condorcet winner and loser criteria, positive involvement (if a candidate $x$ wins in an initial preference profile, then adding a voter who ranks $x$ uniquely first cannot cause $x$ to lose), and resol... | https://arxiv.org/abs/2601.10506 | Academic Papers | svg |
ea9f8a20354c562ca628dabf3bcebfaa85e7e1cb3d69079fc1d172dbb357b616 | 2026-01-16T00:00:00-05:00 | Coarsening Causal DAG Models | arXiv:2601.10531v1 Announce Type: cross Abstract: Directed acyclic graphical (DAG) models are a powerful tool for representing causal relationships among jointly distributed random variables, especially concerning data from across different experimental settings. However, it is not always practical or desirable to esti... | https://arxiv.org/abs/2601.10531 | Academic Papers | svg |
34da02c0f0268950bb7e4a511511f9e8b9d74c4782f3a568287a21ede73a850d | 2026-01-16T00:00:00-05:00 | A Mirror-Descent Algorithm for Computing the Petz-R\'enyi Capacity of Classical-Quantum Channels | arXiv:2601.10558v1 Announce Type: cross Abstract: We study the computation of the $\alpha$-R\'enyi capacity of a classical-quantum (c-q) channel for $\alpha\in(0,1)$. We propose an exponentiated-gradient (mirror descent) iteration that generalizes the Blahut-Arimoto algorithm. Our analysis establishes relative smoothne... | https://arxiv.org/abs/2601.10558 | Academic Papers | svg |
2c853272c465fd03832f43fca2f3c87b6c2a2d217a49845deae22c14a9e22fb9 | 2026-01-16T00:00:00-05:00 | Achievable Degrees of Freedom Analysis and Optimization in Massive MIMO via Characteristic Mode Analysis | arXiv:2601.10576v1 Announce Type: cross Abstract: Massive multiple-input multiple-output (MIMO) is esteemed as a critical technology in 6G communications, providing large degrees of freedom (DoF) to improve multiplexing gain. This paper introduces characteristic mode analysis (CMA) to derive the achievable DoF. Unlike ... | https://arxiv.org/abs/2601.10576 | Academic Papers | svg |
f64044ddd73212725bde46997d9598afb5e6197f83cdbd03ab41e941a8de6db4 | 2026-01-16T00:00:00-05:00 | Searching for Quantum Effects in the Brain: A Bell-Type Test for Nonclassical Latent Representations in Autoencoders | arXiv:2601.10588v1 Announce Type: cross Abstract: Whether neural information processing is entirely classical or involves quantum-mechanical elements remains an open question. Here we propose a model-agnostic, information-theoretic test of nonclassicality that bypasses microscopic assumptions and instead probes the str... | https://arxiv.org/abs/2601.10588 | Academic Papers | svg |
1224af741388de2643f6ec9f5ea7a93baca0fc48178968acc7bba94a456335f9 | 2026-01-16T00:00:00-05:00 | Multi-Objective Pareto-Front Optimization for Efficient Adaptive VVC Streaming | arXiv:2601.10607v1 Announce Type: cross Abstract: Adaptive video streaming has facilitated improved video streaming over the past years. A balance among coding performance objectives such as bitrate, video quality, and decoding complexity is required to achieve efficient, content- and codec-dependent, adaptive video st... | https://arxiv.org/abs/2601.10607 | Academic Papers | svg |
9e0babe25b3404fc486d5ec9dae59a7123605aa0c17ec19aea357c51eb25e389 | 2026-01-16T00:00:00-05:00 | Differentially Private Inference for Longitudinal Linear Regression | arXiv:2601.10626v1 Announce Type: cross Abstract: Differential Privacy (DP) provides a rigorous framework for releasing statistics while protecting individual information present in a dataset. Although substantial progress has been made on differentially private linear regression, existing methods almost exclusively ad... | https://arxiv.org/abs/2601.10626 | Academic Papers | svg |
0135f38a1aa5e50fd956faf3093ca1881db1a1b93aa33dd5336cabc8dd070f7e | 2026-01-16T00:00:00-05:00 | Parametric RDT approach to computational gap of symmetric binary perceptron | arXiv:2601.10628v1 Announce Type: cross Abstract: We study potential presence of statistical-computational gaps (SCG) in symmetric binary perceptrons (SBP) via a parametric utilization of \emph{fully lifted random duality theory} (fl-RDT) [96]. A structural change from decreasingly to arbitrarily ordered $c$-sequence (... | https://arxiv.org/abs/2601.10628 | Academic Papers | svg |
de4c6a20929e35587294dda875ba9108fe809cd1eeaeb9f21f5eda0ca552d967 | 2026-01-16T00:00:00-05:00 | Classification Imbalance as Transfer Learning | arXiv:2601.10630v1 Announce Type: cross Abstract: Classification imbalance arises when one class is much rarer than the other. We frame this setting as transfer learning under label (prior) shift between an imbalanced source distribution induced by the observed data and a balanced target distribution under which perfor... | https://arxiv.org/abs/2601.10630 | Academic Papers | svg |
ccff44838bfe6c96351f902c7714a77111a41d2068a2d4bb6cae1815febbf438 | 2026-01-16T00:00:00-05:00 | Adjusted Similarity Measures and a Violation of Expectations | arXiv:2601.10641v1 Announce Type: cross Abstract: Adjusted similarity measures, such as Cohen's kappa for inter-rater reliability and the adjusted Rand index used to compare clustering algorithms, are a vital tool for comparing discrete labellings. These measures are intended to have the property of 0 expectation under... | https://arxiv.org/abs/2601.10641 | Academic Papers | svg |
4caf6d906d2e3a257752764075b6ec11c62c58d983e1662110a0ad7c004c215f | 2026-01-16T00:00:00-05:00 | Transforming Crises into Opportunities: From Chaos to Urban Antifragility | arXiv:2601.10658v1 Announce Type: cross Abstract: Urban crises - floods, pandemics, economic shocks, and conflicts - function as accelerators of urban change, exposing structural vulnerabilities while creating windows for reinvention. Building on a prior theoretical contribution that identified fifteen principles of ur... | https://arxiv.org/abs/2601.10658 | Academic Papers | svg |
9976fcaa5f77ed901ce40b41fc7f39c27dbc67b46094ddcb1c6015dd002bd1da | 2026-01-16T00:00:00-05:00 | Optimal lower bound for quantum channel tomography in away-from-boundary regime | arXiv:2601.10683v1 Announce Type: cross Abstract: Consider quantum channels with input dimension $d_1$, output dimension $d_2$ and Kraus rank at most $r$. Any such channel must satisfy the constraint $rd_2\geq d_1$, and the parameter regime $rd_2=d_1$ is called the boundary regime. In this paper, we show an optimal que... | https://arxiv.org/abs/2601.10683 | Academic Papers | svg |
ce75962e20db4ef11b27f3426ac336a1ae4b15058867dbd72d6d54b4d74beead | 2026-01-16T00:00:00-05:00 | Constant-Depth Unitary Preparation of Dicke States | arXiv:2601.10693v1 Announce Type: cross Abstract: Dicke states serve as a critical resource in quantum metrology, communication, and computation. However, unitary preparation of Dicke states is limited to logarithmic depth in standard circuit models and existing constant-depth protocols require measurement and feed-for... | https://arxiv.org/abs/2601.10693 | Academic Papers | svg |
46877642c049ea06cf8458ac299e20e88d3fcce0281efa7b0a93fb78115f1a29 | 2026-01-16T00:00:00-05:00 | Quantum Maxwell Erasure Decoder for qLDPC codes | arXiv:2601.10713v1 Announce Type: cross Abstract: We introduce a quantum Maxwell erasure decoder for CSS quantum low-density parity-check (qLDPC) codes that extends peeling with bounded guessing. Guesses are tracked symbolically and can be eliminated by restrictive checks, giving a tunable tradeoff between complexity a... | https://arxiv.org/abs/2601.10713 | Academic Papers | svg |
6195f4e05bc730dcdb1a497c2d1ed2b978467923c9e82c3d52f0b743cfeee148 | 2026-01-16T00:00:00-05:00 | Digital Circuits as Moore Machines | arXiv:1003.0522v2 Announce Type: replace Abstract: This paper illustrates a technique for specifying the timing, logical operation, and compositional circuit design of digital circuits in terms of ordinary state machines with output (Moore machines). The method is illustrated here with specifications of gates, latches,... | https://arxiv.org/abs/1003.0522 | Academic Papers | svg |
966b35310b3f32ba9765789d43245999dc30c700a26090cd010ef7c38805b209 | 2026-01-16T00:00:00-05:00 | Parametric equations for temporal style assertions | arXiv:1612.01630v3 Announce Type: replace Abstract: Temporal logic provided an appealing approach to specifying properties of operating systems and other "reactive" software by allowing propositions to be qualified by "when" they must be true. This paper shows how to get the same effect, with a finer control over speci... | https://arxiv.org/abs/1612.01630 | Academic Papers | svg |
e02e226abe8ac2d2ae858db91f603d5786d197c6b9e6092498b6391c101aebb0 | 2026-01-16T00:00:00-05:00 | Spatial As Deep: Spatial CNN for Traffic Scene Understanding | arXiv:1712.06080v2 Announce Type: replace Abstract: Convolutional neural networks (CNNs) are usually built by stacking convolutional operations layer-by-layer. Although CNN has shown strong capability to extract semantics from raw pixels, its capacity to capture spatial relationships of pixels across rows and columns o... | https://arxiv.org/abs/1712.06080 | Academic Papers | svg |
8d952a265bc594f882c364927e0942ac68c2de991fe125eb10abf586fb1f17e8 | 2026-01-16T00:00:00-05:00 | NFV Platform Design: A Survey | arXiv:2002.11059v4 Announce Type: replace Abstract: Due to the intrinsically inefficient service provisioning in traditional networks, Network Function Virtualization (NFV) keeps gaining attention from both industry and academia. By replacing the purpose-built, expensive, proprietary network equipment with software net... | https://arxiv.org/abs/2002.11059 | Academic Papers | svg |
f73a088afa9164558c45afdcdcb351d06fed7d2ecd8258f9eefb74334a1ccc00 | 2026-01-16T00:00:00-05:00 | Data-Driven Feature Tracking for Event Cameras With and Without Frames | arXiv:2211.12826v4 Announce Type: replace Abstract: Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging scenarios. Existing feature tracking methods for e... | https://arxiv.org/abs/2211.12826 | Academic Papers | svg |
51090f20accb286b96caa0e448d1a8a75ea0c3fe84f06e3c54eaf4fdc3a6c486 | 2026-01-16T00:00:00-05:00 | Genetic Algorithm Based Combinatorial Optimization for the Optimal Design of Water Distribution Network of Gurudeniya Service Zone, Sri Lanka | arXiv:2304.09720v4 Announce Type: replace Abstract: This paper brings an in detail Genetic Algorithm (GA) based combinatorial optimization method used for the optimal design of the water distribution network (WDN) of Gurudeniya Service Zone, Sri Lanka. Genetic Algorithm (GA) mimics the survival of the fittest principle... | https://arxiv.org/abs/2304.09720 | Academic Papers | svg |
8ffb2b9525c8bae3f32e1a7eba0305a314ad309c52ec0a63b8bf9b958bf2303b | 2026-01-16T00:00:00-05:00 | A Kolmogorov metric embedding for live cell microscopy signaling patterns | arXiv:2401.02501v5 Announce Type: replace Abstract: We present a metric embedding that captures spatiotemporal patterns of cell signaling dynamics in 5-D $(x,y,z,channel,time)$ live cell microscopy movies. The embedding uses a metric distance called the normalized information distance (NID) based on Kolmogorov complexi... | https://arxiv.org/abs/2401.02501 | Academic Papers | svg |
f1614bfbd7ce5d8495e34c8a235222801bf6b04317fa6d2c74fff40d493c0378 | 2026-01-16T00:00:00-05:00 | Shadoks Approach to Knapsack Polygonal Packing | arXiv:2403.20123v3 Announce Type: replace Abstract: The 2024 edition of the CG:SHOP Challenge focused on the knapsack polygonal packing problem. Each instance consists of a convex polygon known as the container and a multiset of items, where each item is a simple polygon with an associated integer value. A feasible pac... | https://arxiv.org/abs/2403.20123 | Academic Papers | svg |
c29180c6d3f8cb843333a1804bc07cb4a74886ebf9dac04ad9f1b71a1ebdae53 | 2026-01-16T00:00:00-05:00 | Tuning-Free Adaptive Style Incorporation for Structure-Consistent Text-Driven Style Transfer | arXiv:2404.06835v2 Announce Type: replace Abstract: In this work, we target the task of text-driven style transfer in the context of text-to-image (T2I) diffusion models. The main challenge is consistent structure preservation while enabling effective style transfer effects. The past approaches in this field directly c... | https://arxiv.org/abs/2404.06835 | Academic Papers | svg |
079d0fc0c5c7b81378dd4047ac0843458a6d29e6354253274f4e1c85fdf457ea | 2026-01-16T00:00:00-05:00 | SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning | arXiv:2405.09037v2 Announce Type: replace Abstract: In this work, we propose Salient Sparse Federated Learning (SSFL), a streamlined approach for sparse federated learning with efficient communication. SSFL identifies a sparse subnetwork prior to training, leveraging parameter saliency scores computed separately on loc... | https://arxiv.org/abs/2405.09037 | Academic Papers | svg |
54fbf7be35ec0d0846e2b619426d5e1cf8ab78871f9937ca75f3f1bfc604bb57 | 2026-01-16T00:00:00-05:00 | Jump-teaching: Combating Sample Selection Bias via Temporal Disagreement | arXiv:2405.17137v5 Announce Type: replace Abstract: Sample selection is a straightforward technique to combat noisy labels, aiming to prevent mislabeled samples from degrading the robustness of neural networks. However, existing methods mitigate compounding selection bias either by leveraging dual-network disagreement ... | https://arxiv.org/abs/2405.17137 | Academic Papers | svg |
b7e6e9d0fc622021c16b1b6bdd305561cd8fcc68b76547dae5f06348883c29eb | 2026-01-16T00:00:00-05:00 | Leveraging Open-Source Large Language Models for encoding Social Determinants of Health using an Intelligent Router | arXiv:2405.19631v2 Announce Type: replace Abstract: Social Determinants of Health (SDOH), also known as Health-Related Social Needs (HSRN), play a significant role in patient health outcomes. The Centers for Disease Control and Prevention (CDC) introduced a subset of ICD-10 codes called Z-codes to recognize and measure... | https://arxiv.org/abs/2405.19631 | Academic Papers | svg |
33e24869679c5f3afedcc20c43b7d04658c923d9b62840c2a6261ba72f3c1025 | 2026-01-16T00:00:00-05:00 | AITTI: Learning Adaptive Inclusive Token for Text-to-Image Generation | arXiv:2406.12805v3 Announce Type: replace Abstract: Despite the high-quality results of text-to-image generation, stereotypical biases have been spotted in their generated contents, compromising the fairness of generative models. In this work, we propose to learn adaptive inclusive tokens to shift the attribute distrib... | https://arxiv.org/abs/2406.12805 | Academic Papers | svg |
dfcf644c1f37beca5520b38982776c2fb3853762c0d447cb1b0e704b396a4432 | 2026-01-16T00:00:00-05:00 | Machine Unlearning Fails to Remove Data Poisoning Attacks | arXiv:2406.17216v3 Announce Type: replace Abstract: We revisit the efficacy of several practical methods for approximate machine unlearning developed for large-scale deep learning. In addition to complying with data deletion requests, one often-cited potential application for unlearning methods is to remove the effects... | https://arxiv.org/abs/2406.17216 | Academic Papers | svg |
9660d8c5daca5d37589f6bb0c1616dca1263d1814fce1aeb7ae260b1c02ae17c | 2026-01-16T00:00:00-05:00 | Directed univalence in simplicial homotopy type theory | arXiv:2407.09146v2 Announce Type: replace Abstract: Simplicial type theory extends homotopy type theory with a directed path type which internalizes the notion of a homomorphism within a type. This concept has significant applications both within mathematics -- where it allows for synthetic (higher) category theory -- ... | https://arxiv.org/abs/2407.09146 | Academic Papers | svg |
b7fc324de4b1b19bd423447d61d8c44e61baddb0de37e81ee967ce9af2db61fd | 2026-01-16T00:00:00-05:00 | PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric Agents | arXiv:2407.09394v2 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with generating reliable outputs due to outdated knowledge and hallucinations. Retrieval-Augmented Generation (RAG) models address this by enhancing LLMs with external knowledge, but often fail to personalize the retrieval process... | https://arxiv.org/abs/2407.09394 | Academic Papers | svg |
6229e6d23c4640ce5ba59969b81c30e0aed0dee5af8c06de5dbc9ab9c5fc7b4a | 2026-01-16T00:00:00-05:00 | Mathematical theory of deep learning | arXiv:2407.18384v4 Announce Type: replace Abstract: This book provides an introduction to the mathematical analysis of deep learning. It covers fundamental results in approximation theory, optimization theory, and statistical learning theory, which are the three main pillars of deep neural network theory. Serving as a ... | https://arxiv.org/abs/2407.18384 | Academic Papers | svg |
4de3e13afcc87caf801fb0affed385629c149d9033a18f8ed7132d7eef4c6980 | 2026-01-16T00:00:00-05:00 | Fairness Definitions in Language Models Explained | arXiv:2407.18454v3 Announce Type: replace Abstract: Language Models (LMs) have demonstrated exceptional performance across various Natural Language Processing (NLP) tasks. Despite these advancements, LMs can inherit and amplify societal biases related to sensitive attributes such as gender and race, limiting their adop... | https://arxiv.org/abs/2407.18454 | Academic Papers | svg |
ebddb4152961f9e0b9d40cdc747a29585b84a014f292bc48b1d488481def8a46 | 2026-01-16T00:00:00-05:00 | FiCo-ITR: bridging fine-grained and coarse-grained image-text retrieval for comparative performance analysis | arXiv:2407.20114v2 Announce Type: replace Abstract: In the field of Image-Text Retrieval (ITR), recent advancements have leveraged large-scale Vision-Language Pretraining (VLP) for Fine-Grained (FG) instance-level retrieval, achieving high accuracy at the cost of increased computational complexity. For Coarse-Grained (... | https://arxiv.org/abs/2407.20114 | Academic Papers | svg |
0c05ace63d1f2ecddaed1d6d286e6acd6c9b4a84ac6a7a094551edde777fb5cb | 2026-01-16T00:00:00-05:00 | Controllable Financial Market Generation with Diffusion Guided Meta Agent | arXiv:2408.12991v3 Announce Type: replace Abstract: Generative modeling has transformed many fields, such as language and visual modeling, while its application in financial markets remains under-explored. As the minimal unit within a financial market is an order, order-flow modeling represents a fundamental generative... | https://arxiv.org/abs/2408.12991 | Academic Papers | svg |
dd4835c77f450207bb30d5aaf36a4586fe76307f99061cbe647f3938f24a3510 | 2026-01-16T00:00:00-05:00 | Deep learning-based ecological analysis of camera trap images is impacted by training data quality and quantity | arXiv:2408.14348v3 Announce Type: replace Abstract: Large image collections generated from camera traps offer valuable insights into species richness, occupancy, and activity patterns, significantly aiding biodiversity monitoring. However, the manual processing of these datasets is time-consuming, hindering analytical ... | https://arxiv.org/abs/2408.14348 | Academic Papers | svg |
54ca79a9e57afd1d10fb3533928bfe84a7db1ced7b757bc3b9f4d86f61c26bad | 2026-01-16T00:00:00-05:00 | Uniform Approximation of Eigenproblems of a Large-Scale Parameter-Dependent Hermitian Matrix | arXiv:2409.05791v4 Announce Type: replace Abstract: We consider the uniform approximation of the smallest eigenvalue of a large parameter-dependent Hermitian matrix by that of a smaller counterpart obtained through projections. The projection subspaces are constructed iteratively by means of a greedy strategy; at each ... | https://arxiv.org/abs/2409.05791 | Academic Papers | svg |
224e32ce3534ae27d8b1d1de7011ec91d333d1962f0e5c6244e2d0c4c8377ec2 | 2026-01-16T00:00:00-05:00 | Machine Learning and Theory Ladenness -- A Phenomenological Account | arXiv:2409.11277v2 Announce Type: replace Abstract: We provide an analysis of theory ladenness in machine learning in science, where "theory", that we call "domain theory", refers to the domain knowledge of the scientific discipline where ML is used. By constructing an account of ML models based on a comparison with ph... | https://arxiv.org/abs/2409.11277 | Academic Papers | svg |
41e151517683e1704e76d3c21446c318f3874a0b17d8b8d4596ca8f4fa279dbb | 2026-01-16T00:00:00-05:00 | Debiased Orthogonal Boundary-Driven Efficient Noise Mitigation | arXiv:2410.01944v2 Announce Type: replace Abstract: Mitigating the detrimental effects of noisy labels on the training process has become increasingly critical, as obtaining entirely clean or human-annotated samples for large-scale pre-training tasks is often impractical. Nonetheless, existing noise mitigation methods ... | https://arxiv.org/abs/2410.01944 | Academic Papers | svg |
d2c3020ba58a0eaf197ce16984394895e67fa1c807354f1d3a01cb4b3d6ccb86 | 2026-01-16T00:00:00-05:00 | Permissive Information-Flow Analysis for Large Language Models | arXiv:2410.03055v3 Announce Type: replace Abstract: Large Language Models (LLMs) are rapidly becoming commodity components of larger software systems. This poses natural security and privacy problems: poisoned data retrieved from one component can change the model's behavior and compromise the entire system, including ... | https://arxiv.org/abs/2410.03055 | Academic Papers | svg |
29ab091e98f57b4f38e56cb77a174f5f479a13b017cc0f5efebc07dbe6dfb3d5 | 2026-01-16T00:00:00-05:00 | Finite Element Approximations of Stochastic Linear Schr\"{o}dinger equation driven by additive Wiener noise | arXiv:2410.06006v2 Announce Type: replace Abstract: In this article, we have analyzed semi-discrete finite element approximations of the Stochastic linear Schr\"{o}dinger equation in a bounded convex polygonal domain driven by additive Wiener noise. We use the finite element method for spatial discretization and derive... | https://arxiv.org/abs/2410.06006 | Academic Papers | svg |
ae87aec06a2e33bdbcfb54486ef9b3331d33487f0cb21a568abcff027d898439 | 2026-01-16T00:00:00-05:00 | Developer Needs and Feasible Features for AI Assistants in IDEs | arXiv:2410.08676v3 Announce Type: replace Abstract: Despite the increasing presence of AI assistants in Integrated Development Environments (IDEs), it remains unclear what different groups of developers actually need from these tools and which features are likely to be implemented in practice. To investigate this gap, ... | https://arxiv.org/abs/2410.08676 | Academic Papers | svg |
f0c6d5329a0f85d5b0eedf854ceb3d1b4e66d721cbe1f3c79e3860f35d3eac82 | 2026-01-16T00:00:00-05:00 | CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning | arXiv:2410.10336v2 Announce Type: replace Abstract: Mathematical reasoning remains a significant challenge for large language models (LLMs), despite progress in prompting techniques such as Chain-of-Thought (CoT). We present **Chain of Mathematically Annotated Thought (CoMAT)**, which enhances reasoning through two sta... | https://arxiv.org/abs/2410.10336 | Academic Papers | svg |
7a4b354d3507d88e67b8d8e973697100b5697926efda5993e19885ab4d7e02c4 | 2026-01-16T00:00:00-05:00 | Learning Quadrotor Control From Visual Features Using Differentiable Simulation | arXiv:2410.15979v3 Announce Type: replace Abstract: The sample inefficiency of reinforcement learning (RL) remains a significant challenge in robotics. RL requires large-scale simulation and can still cause long training times, slowing research and innovation. This issue is particularly pronounced in vision-based contr... | https://arxiv.org/abs/2410.15979 | Academic Papers | svg |
5b1eb1450f5b36416039d139518be93ed1afbbe9d343c1a74ec97626e03d01a0 | 2026-01-16T00:00:00-05:00 | Adversarial Multi-Agent Reinforcement Learning for Proactive False Data Injection Detection | arXiv:2411.12130v2 Announce Type: replace Abstract: Smart inverters are instrumental in the integration of distributed energy resources into the electric grid. Such inverters rely on communication layers for continuous control and monitoring, potentially exposing them to cyber-physical attacks such as false data inject... | https://arxiv.org/abs/2411.12130 | Academic Papers | svg |
cb064e5a23345d2e5502f82fdb707cd44e054636aa24148bede0ff4bb7d5800d | 2026-01-16T00:00:00-05:00 | The Hatching-Box: A Novel System for Automated Monitoring and Quantification of Drosophila melanogaster Developmental Behavior | arXiv:2411.15390v4 Announce Type: replace Abstract: In this paper we propose the Hatching-Box, a novel imaging and analysis system to automatically monitor and quantify the developmental behavior of Drosophila in standard rearing vials and during regular rearing routines, rendering explicit experiments obsolete. This i... | https://arxiv.org/abs/2411.15390 | Academic Papers | svg |
a402b2544c858381785959a26515b28774ea049ecad63ce45d480ea2eb3676f1 | 2026-01-16T00:00:00-05:00 | VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics Prediction | arXiv:2411.16063v5 Announce Type: replace Abstract: In-Context Operator Networks (ICONs) have demonstrated the ability to learn operators across diverse partial differential equations using few-shot, in-context learning. However, existing ICONs process each spatial point as an individual token, severely limiting comput... | https://arxiv.org/abs/2411.16063 | Academic Papers | svg |
3d5d4671037aedd56a85ee16dcadc46f93f925662a4b2184217647b3789d383c | 2026-01-16T00:00:00-05:00 | Adaptive Querying for Reward Learning from Human Feedback | arXiv:2412.07990v2 Announce Type: replace Abstract: Learning from human feedback is a popular approach to train robots to adapt to user preferences and improve safety. Existing approaches typically consider a single querying (interaction) format when seeking human feedback and do not leverage multiple modes of user int... | https://arxiv.org/abs/2412.07990 | Academic Papers | svg |
901a8647301b74f69aed6452e7c1cc9b15316e09b848ab7b5bee74c24844f67b | 2026-01-16T00:00:00-05:00 | Singularity-Free Guiding Vector Field over B\'ezier's Curves Applied to Rovers Path Planning and Path Following | arXiv:2412.13033v2 Announce Type: replace Abstract: This paper presents a guidance algorithm for solving the problem of following parametric paths, as well as a curvature-varying speed setpoint for land-based car-type wheeled mobile robots (WMRs). The guidance algorithm relies on Singularity-Free Guiding Vector Fields ... | https://arxiv.org/abs/2412.13033 | Academic Papers | svg |
03bf5a4aca1d8d16ad87277c50d327938917a978b7bb701a2d6fe53619988c4b | 2026-01-16T00:00:00-05:00 | Adaptive Economic Model Predictive Control: Performance Guarantees for Nonlinear Systems | arXiv:2412.13046v3 Announce Type: replace Abstract: We consider the problem of optimizing the economic performance of nonlinear constrained systems subject to uncertain time-varying parameters and bounded disturbances. In particular, we propose an adaptive economic model predictive control (MPC) framework that: (i) dir... | https://arxiv.org/abs/2412.13046 | Academic Papers | svg |
121af327241de97be9020a66c620f2ea961773b17f76b4969d0772f773da2141 | 2026-01-16T00:00:00-05:00 | MatchMiner-AI: An Open-Source Solution for Cancer Clinical Trial Matching | arXiv:2412.17228v3 Announce Type: replace Abstract: Background Clinical trials are essential to advancing cancer treatments, yet fewer than 10% of adults with cancer enroll in trials, and many studies fail to meet accrual targets. Artificial intelligence (AI) could improve identification of appropriate trials for patie... | https://arxiv.org/abs/2412.17228 | Academic Papers | svg |
016f21967aa4078f0db29315eae1d4ee0fb26a37e322b2c146ff82fbdcd61a7f | 2026-01-16T00:00:00-05:00 | Sampling-Based Constrained Motion Planning with Products of Experts | arXiv:2412.17462v2 Announce Type: replace Abstract: We present a novel approach to enhance the performance of sampling-based Model Predictive Control (MPC) in constrained optimization by leveraging products of experts. Our methodology divides the main problem into two components: one focused on optimality and the other... | https://arxiv.org/abs/2412.17462 | Academic Papers | svg |
8213dbb0057138ddb1a6a33177f19ee8b4357acd05b8b6e45ced288bb0be9220 | 2026-01-16T00:00:00-05:00 | Symmetrization Weighted Binary Cross-Entropy: Modeling Perceptual Asymmetry for Human-Consistent Neural Edge Detection | arXiv:2501.13365v3 Announce Type: replace Abstract: Edge detection (ED) is a fundamental perceptual process in computer vision, forming the structural basis for high-level reasoning tasks such as segmentation, recognition, and scene understanding. Despite substantial progress achieved by deep neural networks, most ED m... | https://arxiv.org/abs/2501.13365 | Academic Papers | svg |
381a6eb5e19f952c18629cb1d17c00ed208d60950d7c525db394f3c837797926 | 2026-01-16T00:00:00-05:00 | GreedyPixel: Fine-Grained Black-Box Adversarial Attack Via Greedy Algorithm | arXiv:2501.14230v4 Announce Type: replace Abstract: Deep neural networks are highly vulnerable to adversarial examples, which are inputs with small, carefully crafted perturbations that cause misclassification -- making adversarial attacks a critical tool for evaluating robustness. Existing black-box methods typically ... | https://arxiv.org/abs/2501.14230 | Academic Papers | svg |
5d3fee99c3ee25945eea7dc2a905b19e5950ba8645b39bc6e25f9d36f64169da | 2026-01-16T00:00:00-05:00 | Robust LLM Alignment via Distributionally Robust Direct Preference Optimization | arXiv:2502.01930v4 Announce Type: replace Abstract: A major challenge in aligning large language models (LLMs) with human preferences is the issue of distribution shift. LLM alignment algorithms rely on static preference datasets, assuming that they accurately represent real-world user preferences. However, user prefer... | https://arxiv.org/abs/2502.01930 | Academic Papers | svg |
cc394a7980847e87968d125ae5f6ad600db65a32fca3fd55d2f8db7ccfaeebfa | 2026-01-16T00:00:00-05:00 | CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning | arXiv:2502.03946v2 Announce Type: replace Abstract: Data preprocessing is a critical yet frequently neglected aspect of machine learning, often paid little attention despite its potentially significant impact on model performance. While automated machine learning pipelines are starting to recognize and integrate data p... | https://arxiv.org/abs/2502.03946 | Academic Papers | svg |
7d37015995295bb20af14279172b5094b6c160e737e8c275abbe1335938c393b | 2026-01-16T00:00:00-05:00 | Scalable Oversight for Superhuman AI via Recursive Self-Critiquing | arXiv:2502.04675v4 Announce Type: replace Abstract: As AI capabilities increasingly surpass human proficiency in complex tasks, current alignment techniques, including SFT and RLHF, face fundamental challenges in ensuring reliable oversight. These methods rely on direct human assessment and become impractical when AI o... | https://arxiv.org/abs/2502.04675 | Academic Papers | svg |
222c81f58c3bcc820c8861854bc993f53410587872cfc65a86bdc073b38f8eb6 | 2026-01-16T00:00:00-05:00 | Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images | arXiv:2502.05066v4 Announce Type: replace Abstract: State-of-the-art Diffusion Models (DMs) produce highly realistic images. While prior work has successfully mitigated Not Safe For Work (NSFW) content in the visual domain, we identify a novel threat: the generation of NSFW text embedded within images. This includes of... | https://arxiv.org/abs/2502.05066 | Academic Papers | svg |
4747487242c03d42c3272bfbf1f5fc89aa5efa8f8e257d270abcb50f564e872f | 2026-01-16T00:00:00-05:00 | Online Scheduling for LLM Inference with KV Cache Constraints | arXiv:2502.07115v5 Announce Type: replace Abstract: Large Language Model (LLM) inference, where a trained model generates text one word at a time in response to user prompts, is a computationally intensive process requiring efficient scheduling to optimize latency and resource utilization. A key challenge in LLM infere... | https://arxiv.org/abs/2502.07115 | Academic Papers | svg |
494f14388f2967a90b19fae6b8a1a3b941abe360fd64293274375cfa50bd90d0 | 2026-01-16T00:00:00-05:00 | Curvature Tuning: Provable Training-free Model Steering From a Single Parameter | arXiv:2502.07783v5 Announce Type: replace Abstract: The scaling of model and data sizes has reshaped the AI landscape, establishing finetuning pretrained models as the standard paradigm for solving downstream tasks. However, dominant finetuning methods typically rely on weight adaptation, often lack interpretability, a... | https://arxiv.org/abs/2502.07783 | Academic Papers | svg |
8396aec986185ae8f0f8254d7184a05cc44d6ca563c01b9389486038d5117882 | 2026-01-16T00:00:00-05:00 | When Should a Principal Delegate to an Agent in Selection Processes? | arXiv:2502.07792v2 Announce Type: replace Abstract: Decision-makers in high-stakes selection processes often face a fundamental choice: whether to make decisions themselves or to delegate authority to another entity whose incentives may only be partially aligned with their own. Such delegation arises naturally in setti... | https://arxiv.org/abs/2502.07792 | Academic Papers | svg |
754330a80715b811720fe3e17bd05788d58444ee29667ec871a1f36375b577ec | 2026-01-16T00:00:00-05:00 | Privacy amplification by random allocation | arXiv:2502.08202v4 Announce Type: replace Abstract: We consider the privacy amplification properties of a sampling scheme in which a user's data is used in k steps chosen randomly and uniformly from a sequence (or set) of t steps. This sampling scheme has been recently applied in the context of differentially private o... | https://arxiv.org/abs/2502.08202 | Academic Papers | svg |
e055f2208602ad7d50779186a7e532c32b7f629e0167bfda9acd09691ba5376d | 2026-01-16T00:00:00-05:00 | MixMin: Finding Data Mixtures via Convex Minimization | arXiv:2502.10510v3 Announce Type: replace Abstract: Modern machine learning pipelines are increasingly combining and mixing data from diverse and disparate sources, e.g., pre-training large language models. Yet, finding the optimal data mixture is a challenging and open problem. We formalize this data mixing problem as... | https://arxiv.org/abs/2502.10510 | Academic Papers | svg |
85586efbfecc6cbe50809d954fed8ca5bf3c8c67d883aab941d99f00b2b9efdd | 2026-01-16T00:00:00-05:00 | Exploring the Translation Mechanism of Large Language Models | arXiv:2502.11806v3 Announce Type: replace Abstract: While large language models (LLMs) demonstrate remarkable success in multilingual translation, their internal core translation mechanisms, even at the fundamental word level, remain insufficiently understood. To address this critical gap, this work introduces a system... | https://arxiv.org/abs/2502.11806 | Academic Papers | svg |
6d1db810eef38557e9552b241ce198472f488dd3258e13da2e87d99b4d88ed2e | 2026-01-16T00:00:00-05:00 | LaM-SLidE: Latent Space Modeling of Spatial Dynamical Systems via Linked Entities | arXiv:2502.12128v5 Announce Type: replace Abstract: Generative models are spearheading recent progress in deep learning, showcasing strong promise for trajectory sampling in dynamical systems as well. However, whereas latent space modeling paradigms have transformed image and video generation, similar approaches are mo... | https://arxiv.org/abs/2502.12128 | Academic Papers | svg |
02ab33241879aa72600747c83ec89df56819c705baf78050a082c658bf36050f | 2026-01-16T00:00:00-05:00 | Text Classification Under Class Distribution Shift: A Survey | arXiv:2502.12965v3 Announce Type: replace Abstract: The basic underlying assumption of machine learning (ML) models is that the training and test data are sampled from the same distribution. However, in daily practice, this assumption is often broken, i.e. the distribution of the test data changes over time, which hind... | https://arxiv.org/abs/2502.12965 | Academic Papers | svg |
9d7d710f18c85ef9c15821472fa8a37f1b5e003f02f020031ccf0238d313faf6 | 2026-01-16T00:00:00-05:00 | A Taxonomy for Evaluating Generalist Robot Manipulation Policies | arXiv:2503.01238v2 Announce Type: replace Abstract: Machine learning for robot manipulation promises to unlock generalization to novel tasks and environments. But how should we measure the progress of these policies towards generalization? Evaluating and quantifying generalization is the Wild West of modern robotics, w... | https://arxiv.org/abs/2503.01238 | Academic Papers | svg |
e7de395e4cfdd5bdb29b5c9722a0a7d03c89c60ecb2daa14c446ab761a4c1be4 | 2026-01-16T00:00:00-05:00 | Human-AI Experience in Integrated Development Environments: A Systematic Literature Review | arXiv:2503.06195v3 Announce Type: replace Abstract: The integration of Artificial Intelligence (AI) into Integrated Development Environments (IDEs) is reshaping software development, fundamentally altering how developers interact with their tools. This shift marks the emergence of Human-AI Experience in Integrated Deve... | https://arxiv.org/abs/2503.06195 | Academic Papers | svg |
410de6de63197c554809099cad796533eac8d87b6cca191cd6499c5c2a67f480 | 2026-01-16T00:00:00-05:00 | RS2-SAM2: Customized SAM2 for Referring Remote Sensing Image Segmentation | arXiv:2503.07266v4 Announce Type: replace Abstract: Referring Remote Sensing Image Segmentation (RRSIS) aims to segment target objects in remote sensing (RS) images based on textual descriptions. Although Segment Anything Model 2 (SAM2) has shown remarkable performance in various segmentation tasks, its application to ... | https://arxiv.org/abs/2503.07266 | Academic Papers | svg |
d93ecaea41c879bc9039f9988980da5d7c1a271692902123ae63bb2a210be965 | 2026-01-16T00:00:00-05:00 | High-Quality 3D Head Reconstruction from Any Single Portrait Image | arXiv:2503.08516v3 Announce Type: replace Abstract: In this work, we introduce a novel high-fidelity 3D head reconstruction method from a single portrait image, regardless of perspective, expression, or accessories. Despite significant efforts in adapting 2D generative models for novel view synthesis and 3D optimizatio... | https://arxiv.org/abs/2503.08516 | Academic Papers | svg |
4aca44a56684259c89cb35e20958794b352b79c10768e4e9a545c674d7b54f42 | 2026-01-16T00:00:00-05:00 | ShuffleGate: Scalable Feature Optimization for Recommender Systems via Batch-wise Sensitivity Learning | arXiv:2503.09315v4 Announce Type: replace Abstract: Feature optimization, specifically Feature Selection (FS) and Dimension Selection (DS), is critical for the efficiency and generalization of large-scale recommender systems. While conceptually related, these tasks are typically tackled with isolated solutions that oft... | https://arxiv.org/abs/2503.09315 | Academic Papers | svg |
753efafbf87aeccf65da8098dde791a4d6922d254b21dedab36a9ac3aaf39744 | 2026-01-16T00:00:00-05:00 | TriDF: Triplane-Accelerated Density Fields for Few-Shot Remote Sensing Novel View Synthesis | arXiv:2503.13347v2 Announce Type: replace Abstract: Remote sensing novel view synthesis (NVS) offers significant potential for 3D interpretation of remote sensing scenes, with important applications in urban planning and environmental monitoring. However, remote sensing scenes frequently lack sufficient multi-view imag... | https://arxiv.org/abs/2503.13347 | Academic Papers | svg |
6e6451dbd740b75300facb106f70aec6402db68b8e1e9f120bd9f0acbf360563 | 2026-01-16T00:00:00-05:00 | Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models | arXiv:2503.17523v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as agents that interact with users and with the world. To do so successfully, LLMs must construct representations of the world and form probabilistic beliefs about them. To provide personalized recommendations, for ex... | https://arxiv.org/abs/2503.17523 | Academic Papers | svg |
f89f8e838d941a24920e1b88a3a2101b8900746e19172b41186632c300c1a624 | 2026-01-16T00:00:00-05:00 | CoinFT: A Coin-Sized, Capacitive 6-Axis Force Torque Sensor for Robotic Applications | arXiv:2503.19225v3 Announce Type: replace Abstract: We introduce CoinFT, a capacitive 6-axis force/torque (F/T) sensor that is compact, light, low-cost, and robust with an average root-mean-squared error of 0.16N for force and 1.08mNm for moment when the input ranges from 0~14N and 0~5N in normal and shear directions, ... | https://arxiv.org/abs/2503.19225 | Academic Papers | svg |
4e7f34dfc28af7251476903c88e8e24c988ff2634359e2e73fecd44a6417e53e | 2026-01-16T00:00:00-05:00 | Testing Low-Resource Language Support in LLMs Using Language Proficiency Exams: the Case of Luxembourgish | arXiv:2504.01667v4 Announce Type: replace Abstract: Large Language Models (LLMs) have become an increasingly important tool in research and society at large. While LLMs are regularly used all over the world by experts and lay-people alike, they are predominantly developed with English-speaking users in mind, performing... | https://arxiv.org/abs/2504.01667 | Academic Papers | svg |
df319912355c04cbce325b058401caa62f7b20838b72cd7a51dc9b47fbde0638 | 2026-01-16T00:00:00-05:00 | Barrier Certificates for Unknown Systems with Latent States and Polynomial Dynamics using Bayesian Inference | arXiv:2504.01807v3 Announce Type: replace Abstract: Certifying safety in dynamical systems is crucial, but barrier certificates - widely used to verify that system trajectories remain within a safe region - typically require explicit system models. When dynamics are unknown, data-driven methods can be used instead, yet... | https://arxiv.org/abs/2504.01807 | Academic Papers | svg |
0862764c277bce35815b160680b56c254e056fb4212cc6192f40f0ab3a147008 | 2026-01-16T00:00:00-05:00 | A vector bundle approach to Nash equilibria | arXiv:2504.03456v2 Announce Type: replace Abstract: We use vector bundles to study the locus of totally mixed Nash equilibria of an $n$-player game in normal form, which we call the Nash equilibrium scheme. When the payoff tensor format is balanced, we study the Nash discriminant variety, i.e., the algebraic variety of... | https://arxiv.org/abs/2504.03456 | Academic Papers | svg |
5b092ca999c196adbe416d7fc2692630084dc7b38d3c94fbeacfe14a099ada9e | 2026-01-16T00:00:00-05:00 | Evaluating Large Language Models for Fair and Reliable Organ Allocation | arXiv:2504.03716v2 Announce Type: replace Abstract: Medical institutions are considering the use of LLMs in high-stakes clinical decision-making, such as organ allocation. In such sensitive use cases, evaluating fairness is imperative. However, existing evaluation methods often fall short; benchmarks are too simplistic... | https://arxiv.org/abs/2504.03716 | Academic Papers | svg |
f91727b72fee72b7e5f7fbdac44671f5cd7b6a52cfedb384e056e5b0587ed673 | 2026-01-16T00:00:00-05:00 | WebRollback: Enhancing Web Agents with Explicit Rollback Mechanisms | arXiv:2504.11788v3 Announce Type: replace Abstract: With recent advancements in large language models, web agents have been greatly improved. However, dealing with complex and dynamic web environments requires more advanced planning and search abilities. Previous studies usually adopt a greedy one-way search strategy, ... | https://arxiv.org/abs/2504.11788 | Academic Papers | svg |
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