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faebfa3a7418f0ffbec0f2de1e4ba41d36eb27b5161b7b93ebacf0bc83c68c8c | 2026-01-23T00:00:00-05:00 | HyperAlign: Hypernetwork for Efficient Test-Time Alignment of Diffusion Models | arXiv:2601.15968v1 Announce Type: new Abstract: Diffusion models achieve state-of-the-art performance but often fail to generate outputs that align with human preferences and intentions, resulting in images with poor aesthetic quality and semantic inconsistencies. Existing alignment methods present a difficult trade-of... | https://arxiv.org/abs/2601.15968 | Academic Papers | svg |
780a4893de155295cd1cdce60541ab420bcd7e5fd223e11ca816da0645ac852e | 2026-01-23T00:00:00-05:00 | Unveiling and Simulating Short-Video Addiction Behaviors via Economic Addiction Theory | arXiv:2601.15975v1 Announce Type: new Abstract: Short-video applications have attracted substantial user traffic. However, these platforms also foster problematic usage patterns, commonly referred to as short-video addiction, which pose risks to both user health and the sustainable development of platforms. Prior studi... | https://arxiv.org/abs/2601.15975 | Academic Papers | svg |
57e2c7124c40c244d5225ffaf400be8e7e6fbcdb72be7675b12dbaf41a4e8ac8 | 2026-01-23T00:00:00-05:00 | Predicting Healthcare System Visitation Flow by Integrating Hospital Attributes and Population Socioeconomics with Human Mobility Data | arXiv:2601.15977v1 Announce Type: new Abstract: Healthcare visitation patterns are influenced by a complex interplay of hospital attributes, population socioeconomics, and spatial factors. However, existing research often adopts a fragmented approach, examining these determinants in isolation. This study addresses this... | https://arxiv.org/abs/2601.15977 | Academic Papers | svg |
1b7cdb035685bfe72add5c38eaa9f6400c4f789f942075bbd458d5390d2f0bb8 | 2026-01-23T00:00:00-05:00 | Partially Lazy Gradient Descent for Smoothed Online Learning | arXiv:2601.15984v1 Announce Type: new Abstract: We introduce $k$-lazyGD, an online learning algorithm that bridges the gap between greedy Online Gradient Descent (OGD, for $k=1$) and lazy GD/dual-averaging (for $k=T$), creating a spectrum between reactive and stable updates. We analyze this spectrum in Smoothed Online ... | https://arxiv.org/abs/2601.15984 | Academic Papers | svg |
02f3eadfb0f203216b6fdfe44d58894d9b35f84b2cfa8334c5e4a08ea05e12a5 | 2026-01-23T00:00:00-05:00 | Efficient Cloud-edge Collaborative Approaches to SPARQL Queries over Large RDF graphs | arXiv:2601.15992v1 Announce Type: new Abstract: With the increasing use of RDF graphs, storing and querying such data using SPARQL remains a critical problem. Current mainstream solutions rely on cloud-based data management architectures, but often suffer from performance bottle- necks in environments with limited band... | https://arxiv.org/abs/2601.15992 | Academic Papers | svg |
6c034e4cd3436b069f70e6023a595c202b135a3b1f461bf07ab90c3aa559ca03 | 2026-01-23T00:00:00-05:00 | PUMA: Perception-driven Unified Foothold Prior for Mobility Augmented Quadruped Parkour | arXiv:2601.15995v1 Announce Type: new Abstract: Parkour tasks for quadrupeds have emerged as a promising benchmark for agile locomotion. While human athletes can effectively perceive environmental characteristics to select appropriate footholds for obstacle traversal, endowing legged robots with similar perceptual reas... | https://arxiv.org/abs/2601.15995 | Academic Papers | svg |
a2a941fc07e79cbedaf4fa8dc56e8581ac6298f217e97e7c001b51a985c69f19 | 2026-01-23T00:00:00-05:00 | PhysicsMind: Sim and Real Mechanics Benchmarking for Physical Reasoning and Prediction in Foundational VLMs and World Models | arXiv:2601.16007v1 Announce Type: new Abstract: Modern foundational Multimodal Large Language Models (MLLMs) and video world models have advanced significantly in mathematical, common-sense, and visual reasoning, but their grasp of the underlying physics remains underexplored. Existing benchmarks attempting to measure ... | https://arxiv.org/abs/2601.16007 | Academic Papers | svg |
7003c821165190c4889aa4a0cb3fa3917ac56357c9df757e6e5aaedfc48b719e | 2026-01-23T00:00:00-05:00 | Prioritizing Configuration Relevance via Compiler-Based Refined Feature Ranking | arXiv:2601.16008v1 Announce Type: new Abstract: Modern programming languages, most notably Rust, offer advanced linguistic constructs for building highly configurable software systems as aggregation of features -- identified by a configuration. However, they pose substantial challenges for program analysis, optimizatio... | https://arxiv.org/abs/2601.16008 | Academic Papers | svg |
d3270b1f9f5fd77cbc754c973ea9f81ceb33ca336711772ab7b17d4b51f0c843 | 2026-01-23T00:00:00-05:00 | The Role of Cognitive Abilities in Requirements Inspection: Comparing UML and Textual Representations | arXiv:2601.16009v1 Announce Type: new Abstract: The representation of requirements plays a critical role in the accuracy of requirements inspection. While visual representations, such as UML diagrams, are widely used alongside text-based requirements, their effectiveness in supporting inspection is still debated. Cogni... | https://arxiv.org/abs/2601.16009 | Academic Papers | svg |
68d46485116f4645cd941702b4a3b95086238a6e275ea8f44242139922078b57 | 2026-01-23T00:00:00-05:00 | Stability Analysis of Power-Electronics-Dominated Grids Using Scaled Relative Graphs | arXiv:2601.16014v1 Announce Type: new Abstract: This paper presents a novel approach to stability analysis for grid-connected converters utilizing Scaled Relative Graphs (SRG). Our method effectively decouples grid and converter dynamics, thereby establishing a comprehensive and efficient framework for evaluating close... | https://arxiv.org/abs/2601.16014 | Academic Papers | svg |
c67acc971c0839d343d7420a39d02f7b5440ae1d9a103fd6815c1b7ad515c5f3 | 2026-01-23T00:00:00-05:00 | Mecellem Models: Turkish Models Trained from Scratch and Continually Pre-trained for the Legal Domain | arXiv:2601.16018v1 Announce Type: new Abstract: This paper presents Mecellem models, a framework for developing specialized language models for the Turkish legal domain through domain adaptation strategies. We make two contributions: (1)Encoder Model Pre-trained from Scratch: ModernBERT-based bidirectional encoders pre... | https://arxiv.org/abs/2601.16018 | Academic Papers | svg |
f8b7b64460c261771356e13c1898ad07eba1f1f26d83d4a01470f3901de1acd7 | 2026-01-23T00:00:00-05:00 | Keyframe-Based Feed-Forward Visual Odometry | arXiv:2601.16020v1 Announce Type: new Abstract: The emergence of visual foundation models has revolutionized visual odometry~(VO) and SLAM, enabling pose estimation and dense reconstruction within a single feed-forward network. However, unlike traditional pipelines that leverage keyframe methods to enhance efficiency a... | https://arxiv.org/abs/2601.16020 | Academic Papers | svg |
cb37a5f573f0c686e8c0614e850e9f41d5de8468607f946ec4240967ab87966b | 2026-01-23T00:00:00-05:00 | PAINT: Pathology-Aware Integrated Next-Scale Transformation for Virtual Immunohistochemistry | arXiv:2601.16024v1 Announce Type: new Abstract: Virtual immunohistochemistry (IHC) aims to computationally synthesize molecular staining patterns from routine Hematoxylin and Eosin (H\&E) images, offering a cost-effective and tissue-efficient alternative to traditional physical staining. However, this task is parti... | https://arxiv.org/abs/2601.16024 | Academic Papers | svg |
58fa699754a1b44068e95016748079f141fe181e280da4416f4043347281fae9 | 2026-01-23T00:00:00-05:00 | EAIFD: A Fast and Scalable Algorithm for Incremental Functional Dependency Discovery | arXiv:2601.16025v1 Announce Type: new Abstract: Functional dependencies (FDs) are fundamental integrity constraints in relational databases, but discovering them under incremental updates remains challenging. While static algorithms are inefficient due to full re-execution, incremental algorithms suffer from severe per... | https://arxiv.org/abs/2601.16025 | Academic Papers | svg |
44fca4e7d97cd3ea5c21f78125e05b0a27bb6d868d5fc96485d6d680b259bf3a | 2026-01-23T00:00:00-05:00 | Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment | arXiv:2601.16027v1 Announce Type: new Abstract: The rise of live streaming has transformed online interaction, enabling massive real-time engagement but also exposing platforms to complex risks such as scams and coordinated malicious behaviors. Detecting these risks is challenging because harmful actions often accumula... | https://arxiv.org/abs/2601.16027 | Academic Papers | svg |
23d5e36e82ba6eed9b417a2352ccd4e709c67f05b85efe640d0d2591f61f618f | 2026-01-23T00:00:00-05:00 | Data-Driven Conditional Flexibility Index | arXiv:2601.16028v1 Announce Type: new Abstract: With the increasing flexibilization of processes, determining robust scheduling decisions has become an important goal. Traditionally, the flexibility index has been used to identify safe operating schedules by approximating the admissible uncertainty region using simple ... | https://arxiv.org/abs/2601.16028 | Academic Papers | svg |
6bf2cfaaa15f608c1b4e0a5bb727df59a51f6aff0727e798eba0fe70b983274f | 2026-01-23T00:00:00-05:00 | Stacked Intelligent Metasurface-Aided Wave-Domain Signal Processing: From Communications to Sensing and Computing | arXiv:2601.16030v1 Announce Type: new Abstract: Neural networks possess incredible capabilities for extracting abstract features from data. Electromagnetic computing harnesses wave propagation to execute computational operations. Metasurfaces, composed of subwavelength meta-atoms, are capable of engineering electromagn... | https://arxiv.org/abs/2601.16030 | Academic Papers | svg |
45c3371bab8d222d1a63695c04c7a570df521edb4039f3529155d58319496c31 | 2026-01-23T00:00:00-05:00 | Sawtooth Wavefront Reordering: Enhanced CuTile FlashAttention on NVIDIA GB10 | arXiv:2601.16032v1 Announce Type: new Abstract: High-performance attention kernels are essential for Large Language Models. This paper presents analysis of CuTile-based Flash Attention memory behavior and a technique to improve its cache performance. In particular, our analysis on the NVIDIA GB10 (Grace Blackwell) iden... | https://arxiv.org/abs/2601.16032 | Academic Papers | svg |
d8fff9a484c59f5477c873cda8900251d2caf92fd76c9e3618b24490e7cea0d0 | 2026-01-23T00:00:00-05:00 | RIS-Aided Cooperative ISAC Network for Imaging-Based Low-Altitude Surveillance | arXiv:2601.16033v1 Announce Type: new Abstract: The low-altitude economy is integral to the advancement of numerous sectors, necessitating the development of advanced low-altitude surveillance techniques. Nevertheless, conventional methods encounter limitations of high deployment costs and low signal strength. This stu... | https://arxiv.org/abs/2601.16033 | Academic Papers | svg |
867a4bc50fe41ec70f4bdfb12c502fa2910f9d7a75009ac7e46b221aa2182550 | 2026-01-23T00:00:00-05:00 | Universal Refusal Circuits Across LLMs: Cross-Model Transfer via Trajectory Replay and Concept-Basis Reconstruction | arXiv:2601.16034v1 Announce Type: new Abstract: Refusal behavior in aligned LLMs is often viewed as model-specific, yet we hypothesize it stems from a universal, low-dimensional semantic circuit shared across models. To test this, we introduce Trajectory Replay via Concept-Basis Reconstruction, a framework that transfe... | https://arxiv.org/abs/2601.16034 | Academic Papers | svg |
5fbd91e53198e1f70a58748496e4ad123dc363fed08fc3a66394676e83003a4b | 2026-01-23T00:00:00-05:00 | Collision-Free Humanoid Traversal in Cluttered Indoor Scenes | arXiv:2601.16035v1 Announce Type: new Abstract: We study the problem of collision-free humanoid traversal in cluttered indoor scenes, such as hurdling over objects scattered on the floor, crouching under low-hanging obstacles, or squeezing through narrow passages. To achieve this goal, the humanoid needs to map its per... | https://arxiv.org/abs/2601.16035 | Academic Papers | svg |
51b8febb1f89451c0e354a091e6bf316769d6bfbf9fefc0df5182976c6fc47ff | 2026-01-23T00:00:00-05:00 | Tri-Hybrid Beamforming Design for integrated Sensing and Communications | arXiv:2601.16036v1 Announce Type: new Abstract: Tri-hybrid beamforming architectures have been proposed to enable energy-efficient communications systems in extra-largescale antenna arrays using low-cost programmable metasurface antennas. We study the tri-hybrid beamforming design for integrated sensing and communicati... | https://arxiv.org/abs/2601.16036 | Academic Papers | svg |
9b7f12cb32c7d3aa3ad4a3752b1850587676ae3aef0dd4fa8c70dcc255bdb6de | 2026-01-23T00:00:00-05:00 | Grounding Large Language Models in Reaction Knowledge Graphs for Synthesis Retrieval | arXiv:2601.16038v1 Announce Type: new Abstract: Large Language Models (LLMs) can aid synthesis planning in chemistry, but standard prompting methods often yield hallucinated or outdated suggestions. We study LLM interactions with a reaction knowledge graph by casting reaction path retrieval as a Text2Cypher (natural la... | https://arxiv.org/abs/2601.16038 | Academic Papers | svg |
f8fd92506e799eb443e9e9096b28df0b08c60122a59e3e64363c61c4a9f0c954 | 2026-01-23T00:00:00-05:00 | Characterizations of monadically dependent tree-ordered weakly sparse structures | arXiv:2601.16039v1 Announce Type: new Abstract: A class of structures is monadically dependent if one cannot interpret all graphs in colored expansions from the class using a fixed first-order formula. A tree-ordered $\sigma$-structure is the expansion of a $\sigma$-structure with a tree-order. A tree-ordered $\sigma$-... | https://arxiv.org/abs/2601.16039 | Academic Papers | svg |
05fe72763edab8000afae4c8dc0578d0358da613da271a6c73922bddf1a1dda8 | 2026-01-23T00:00:00-05:00 | Can Platform Design Encourage Curiosity? Evidence from an Independent Social Media Experiment | arXiv:2601.16040v1 Announce Type: new Abstract: Social media platforms are often criticized for fostering antisocial behavior rather than prosocial behavior. Yet, testing interventions to encourage prosocial dispositions, such as open-mindedness, has been hindered by researchers' limited ability to manipulate platform ... | https://arxiv.org/abs/2601.16040 | Academic Papers | svg |
3aecf066ba4ab8d6a6da06af86ce9306f93fd2a7fe66ae9c9d153d7bc41ef7b7 | 2026-01-23T00:00:00-05:00 | AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress | arXiv:2601.16045v1 Announce Type: new Abstract: Accurate prediction of crop above-ground biomass (AGB) under water stress is critical for monitoring crop productivity, guiding irrigation, and supporting climate-resilient agriculture. Data-driven models scale well but often lack interpretability and degrade under distri... | https://arxiv.org/abs/2601.16045 | Academic Papers | svg |
807157c6b6037e3312c3d095a05f4d4f2308ae0e8c95af5ddce577dc172dc37f | 2026-01-23T00:00:00-05:00 | DextER: Language-driven Dexterous Grasp Generation with Embodied Reasoning | arXiv:2601.16046v1 Announce Type: new Abstract: Language-driven dexterous grasp generation requires the models to understand task semantics, 3D geometry, and complex hand-object interactions. While vision-language models have been applied to this problem, existing approaches directly map observations to grasp parameter... | https://arxiv.org/abs/2601.16046 | Academic Papers | svg |
5f8e9e3c54f3f403e549d430e22961d714742b1b8f6a28dd75b146716514d09d | 2026-01-23T00:00:00-05:00 | From Harm to Healing: Understanding Individual Resilience after Cybercrimes | arXiv:2601.16050v1 Announce Type: new Abstract: How do individuals recover from cybercrimes? Victims experience various types of harm after cybercrimes, including monetary loss, data breaches, negative emotions, and even psychological trauma. The aspects that support their recovery process and contribute to individual ... | https://arxiv.org/abs/2601.16050 | Academic Papers | svg |
18d1d70beae61e18c69d3442b540206333919cc9b9427bbf1dcd35439fb9428c | 2026-01-23T00:00:00-05:00 | Designing faster mixed integer linear programming algorithm via learning the optimal path | arXiv:2601.16056v1 Announce Type: new Abstract: Designing faster algorithms for solving Mixed-Integer Linear Programming (MILP) problems is highly desired across numerous practical domains, as a vast array of complex real-world challenges can be effectively modeled as MILP formulations. Solving these problems typically... | https://arxiv.org/abs/2601.16056 | Academic Papers | svg |
145a9998c3b728eb1e49f5f4b7014aa4472c69dea1161529503e5d7239435b83 | 2026-01-23T00:00:00-05:00 | ProGiDiff: Prompt-Guided Diffusion-Based Medical Image Segmentation | arXiv:2601.16060v1 Announce Type: new Abstract: Widely adopted medical image segmentation methods, although efficient, are primarily deterministic and remain poorly amenable to natural language prompts. Thus, they lack the capability to estimate multiple proposals, human interaction, and cross-modality adaptation. Rece... | https://arxiv.org/abs/2601.16060 | Academic Papers | svg |
294447c844a408a9d7980c9046fe9a19aab319200fd150068a954c636226baf9 | 2026-01-23T00:00:00-05:00 | Dynamic Tactile Sensing System and Soft Actor Critic Reinforcement Learning for Inclusion Characterization | arXiv:2601.16061v1 Announce Type: new Abstract: This paper presents the Dynamic Tactile Sensing System that utilizes robotic tactile sensing in conjunction with reinforcement learning to locate and characterize embedded inclusions. A dual arm robot is integrated with an optical Tactile Imaging Sensor that utilizes the ... | https://arxiv.org/abs/2601.16061 | Academic Papers | svg |
b623bcfb3a0995887e04b0000444fd817a30d69c14612431bb06f5c649ccc151 | 2026-01-23T00:00:00-05:00 | Improve the autonomy of the SE2(3) group based Extended Kalman Filter for Integrated Navigation: Theoretical Analysis | arXiv:2601.16062v1 Announce Type: new Abstract: One of core advantages of the SE2(3) Lie group framework for navigation modeling lies in the autonomy of error propagation. Current research on Lie group based extended Kalman filters has demonstrated that error propagation autonomy holds in low-precision applications, su... | https://arxiv.org/abs/2601.16062 | Academic Papers | svg |
c355af06a1d902dfe01f94f040daf5e0b12e3661ea7658cc4f5fdaf0e30f3430 | 2026-01-23T00:00:00-05:00 | DTP: A Simple yet Effective Distracting Token Pruning Framework for Vision-Language Action Models | arXiv:2601.16065v1 Announce Type: new Abstract: Vision-Language Action (VLA) models have shown remarkable progress in robotic manipulation by leveraging the powerful perception abilities of Vision-Language Models (VLMs) to understand environments and directly output actions. However, by default, VLA models may overly a... | https://arxiv.org/abs/2601.16065 | Academic Papers | svg |
ebfda98de4b2f5f1c66dd15f57653a7ada09eabe2117f90d056b95d83cd4f0c0 | 2026-01-23T00:00:00-05:00 | CLASP: An online learning algorithm for Convex Losses And Squared Penalties | arXiv:2601.16072v1 Announce Type: new Abstract: We study Constrained Online Convex Optimization (COCO), where a learner chooses actions iteratively, observes both unanticipated convex loss and convex constraint, and accumulates loss while incurring penalties for constraint violations. We introduce CLASP (Convex Losses ... | https://arxiv.org/abs/2601.16072 | Academic Papers | svg |
ac815399ebdd845b206f0ac81201fc6aa145c09b425b24d2fd7e50970f0edeca | 2026-01-23T00:00:00-05:00 | DSFedMed: Dual-Scale Federated Medical Image Segmentation via Mutual Distillation Between Foundation and Lightweight Models | arXiv:2601.16073v1 Announce Type: new Abstract: Foundation Models (FMs) have demonstrated strong generalization across diverse vision tasks. However, their deployment in federated settings is hindered by high computational demands, substantial communication overhead, and significant inference costs. We propose DSFedMed... | https://arxiv.org/abs/2601.16073 | Academic Papers | svg |
acb63fbabd929a813d7984a68234f0633823dbe051570be19d1bc495e9ad2fcc | 2026-01-23T00:00:00-05:00 | Explainable AI to Improve Machine Learning Reliability for Industrial Cyber-Physical Systems | arXiv:2601.16074v1 Announce Type: new Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability critically important. Machine Learning (ML), specifically deep learning, is increasingly integrated in industrial CPS, but the inhere... | https://arxiv.org/abs/2601.16074 | Academic Papers | svg |
b679abcb72aeadc6b68e542a4e4eda6799d0822565328428ce4d7e7ff3b84035 | 2026-01-23T00:00:00-05:00 | DNF formulas are efficiently testable with relative error | arXiv:2601.16076v1 Announce Type: new Abstract: We give a poly$(s,1/\epsilon)$-query algorithm for testing whether an unknown and arbitrary function $f: \{0,1\}^n \to \{0,1\}$ is an $s$-term DNF, in the challenging relative-error framework for Boolean function property testing that was recently introduced and studied i... | https://arxiv.org/abs/2601.16076 | Academic Papers | svg |
bae88c0af728c8b08919b8dc4c09a405612257fe40c3c202737cd608edb37310 | 2026-01-23T00:00:00-05:00 | Improve the autonomy of the SE2(3) group based Extended Kalman Filter for Integrated Navigation: Application | arXiv:2601.16078v1 Announce Type: new Abstract: One of the core advantages of SE2(3) Lie group framework for navigation modeling lies in the autonomy of error propagation. In the previous paper, the theoretical analysis of autonomy property of navigation model in inertial, earth and world frames was given. A constructi... | https://arxiv.org/abs/2601.16078 | Academic Papers | svg |
89b33a45f39074a788e977818da315b368ffaf07daecc08d68bdd6c01b96ea27 | 2026-01-23T00:00:00-05:00 | Masked Modeling for Human Motion Recovery Under Occlusions | arXiv:2601.16079v1 Announce Type: new Abstract: Human motion reconstruction from monocular videos is a fundamental challenge in computer vision, with broad applications in AR/VR, robotics, and digital content creation, but remains challenging under frequent occlusions in real-world settings.Existing regression-based me... | https://arxiv.org/abs/2601.16079 | Academic Papers | svg |
6272dd1c42c1a169c666c1bb2dd3d392a512d3190818976efe441988cf8f3160 | 2026-01-23T00:00:00-05:00 | Towards a Goal-Centric Assessment of Requirements Engineering Methods for Privacy by Design | arXiv:2601.16080v1 Announce Type: new Abstract: Implementing privacy by design (PbD) according to the General Data Protection Regulation (GDPR) is met with a growing number of requirements engineering (RE) approaches. However, the question of which RE method for PbD fits best the goals of organisations remains a challe... | https://arxiv.org/abs/2601.16080 | Academic Papers | svg |
699b599862283c79607d37ff23efb6456cb36ccf06e9dcdbc7277389d1a1cc6e | 2026-01-23T00:00:00-05:00 | Probably Approximately Correct Maximum A Posteriori Inference | arXiv:2601.16083v1 Announce Type: new Abstract: Computing the conditional mode of a distribution, better known as the $\mathit{maximum\ a\ posteriori}$ (MAP) assignment, is a fundamental task in probabilistic inference. However, MAP estimation is generally intractable, and remains hard even under many common structural... | https://arxiv.org/abs/2601.16083 | Academic Papers | svg |
7981572240e6e79849efd7b6e1611c6a41eb8ee68832bfd717032b293d141f2f | 2026-01-23T00:00:00-05:00 | Controlling Long-Horizon Behavior in Language Model Agents with Explicit State Dynamics | arXiv:2601.16087v1 Announce Type: new Abstract: Large language model (LLM) agents often exhibit abrupt shifts in tone and persona during extended interaction, reflecting the absence of explicit temporal structure governing agent-level state. While prior work emphasizes turn-local sentiment or static emotion classificat... | https://arxiv.org/abs/2601.16087 | Academic Papers | svg |
3bb769ac0b1c396696112ac6ee6a62d3e2b100c2670cc64da1e505f304fb2f94 | 2026-01-23T00:00:00-05:00 | Delayed Assignments in Online Non-Centroid Clustering with Stochastic Arrivals | arXiv:2601.16091v1 Announce Type: new Abstract: Clustering is a fundamental problem, aiming to partition a set of elements, like agents or data points, into clusters such that elements in the same cluster are closer to each other than to those in other clusters. In this paper, we present a new framework for studying on... | https://arxiv.org/abs/2601.16091 | Academic Papers | svg |
1e2e4e694573f54f750c28d4056cca60145e883b41042402d910a74aa287ef8c | 2026-01-23T00:00:00-05:00 | SAMTok: Representing Any Mask with Two Words | arXiv:2601.16093v1 Announce Type: new Abstract: Pixel-wise capabilities are essential for building interactive intelligent systems. However, pixel-wise multi-modal LLMs (MLLMs) remain difficult to scale due to complex region-level encoders, specialized segmentation decoders, and incompatible training objectives. To add... | https://arxiv.org/abs/2601.16093 | Academic Papers | svg |
b9c69db1b862fdf0b90f4917ed0556398ca630bf552993096934fc2d1b08adfb | 2026-01-23T00:00:00-05:00 | Neural Particle Automata: Learning Self-Organizing Particle Dynamics | arXiv:2601.16096v1 Announce Type: new Abstract: We introduce Neural Particle Automata (NPA), a Lagrangian generalization of Neural Cellular Automata (NCA) from static lattices to dynamic particle systems. Unlike classical Eulerian NCA where cells are pinned to pixels or voxels, NPA model each cell as a particle with a ... | https://arxiv.org/abs/2601.16096 | Academic Papers | svg |
901a74c28c8b42c11e813e747787826f1cd2f2d79daa61797ee3c987d22dd297 | 2026-01-23T00:00:00-05:00 | Adapter Fusion for Multilingual Text2Cypher with Linear and Learned Gating | arXiv:2601.16097v1 Announce Type: new Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, which translate user questions into structured database queries. While these systems improve database accessibility, most resea... | https://arxiv.org/abs/2601.16097 | Academic Papers | svg |
0faf76e7fa904c5238e5b3d5fa70db311810bf69babbf5470a0ee7432fce8ff3 | 2026-01-23T00:00:00-05:00 | Clustering-Guided Spatial-Spectral Mamba for Hyperspectral Image Classification | arXiv:2601.16098v1 Announce Type: new Abstract: Although Mamba models greatly improve Hyperspectral Image (HSI) classification, they have critical challenges in terms defining efficient and adaptive token sequences for improve performance. This paper therefore presents CSSMamba (Clustering-guided Spatial-Spectral Mamba... | https://arxiv.org/abs/2601.16098 | Academic Papers | svg |
1471a832bf75aff8a259b8313ab1366e54dc70b53f099405f5733d5a4f8bdbfb | 2026-01-23T00:00:00-05:00 | Benchmarking Deep Learning Models for Raman Spectroscopy Across Open-Source Datasets | arXiv:2601.16107v1 Announce Type: new Abstract: Deep learning classifiers for Raman spectroscopy are increasingly reported to outperform classical chemometric approaches. However their evaluations are often conducted in isolation or compared against traditional machine learning methods or trivially adapted vision-based... | https://arxiv.org/abs/2601.16107 | Academic Papers | svg |
9f5f77038e75d386ec69248fde65925b6a8e3c633029e04d34764a44ef5ded9c | 2026-01-23T00:00:00-05:00 | Multimodal Climate Disinformation Detection: Integrating Vision-Language Models with External Knowledge Sources | arXiv:2601.16108v1 Announce Type: new Abstract: Climate disinformation has become a major challenge in today digital world, especially with the rise of misleading images and videos shared widely on social media. These false claims are often convincing and difficult to detect, which can delay actions on climate change. ... | https://arxiv.org/abs/2601.16108 | Academic Papers | svg |
312e153a9742eb5b5820511792b3d625949e9f43adb567b7041217241ba26376 | 2026-01-23T00:00:00-05:00 | Efficiently Learning Robust Torque-based Locomotion Through Reinforcement with Model-Based Supervision | arXiv:2601.16109v1 Announce Type: new Abstract: We propose a control framework that integrates model-based bipedal locomotion with residual reinforcement learning (RL) to achieve robust and adaptive walking in the presence of real-world uncertainties. Our approach leverages a model-based controller, comprising a Diverg... | https://arxiv.org/abs/2601.16109 | Academic Papers | svg |
7b8a23dfcbb79ab65ea99001776fb31bffba86c9d3d8785c46726fca57bcf5e9 | 2026-01-23T00:00:00-05:00 | Variable Splitting Binary Tree Models Based on Bayesian Context Tree Models for Time Series Segmentation | arXiv:2601.16112v1 Announce Type: new Abstract: We propose a variable splitting binary tree (VSBT) model based on Bayesian context tree (BCT) models for time series segmentation. Unlike previous applications of BCT models, the tree structure in our model represents interval partitioning on the time domain. Moreover, in... | https://arxiv.org/abs/2601.16112 | Academic Papers | svg |
1c2ea8cba23ee9e9fdddaf93c571af3fe23c3b0956f154c7c61683f58fee9da0 | 2026-01-23T00:00:00-05:00 | synthocr-gen: A synthetic ocr dataset generator for low-resource languages- breaking the data barrier | arXiv:2601.16113v1 Announce Type: new Abstract: Optical Character Recognition (OCR) for low-resource languages remains a significant challenge due to the scarcity of large-scale annotated training datasets. Languages such as Kashmiri, with approximately 7 million speakers and a complex Perso-Arabic script featuring uni... | https://arxiv.org/abs/2601.16113 | Academic Papers | svg |
bc322896488cf685d0d15fac50e05bf4bcfb30804215407d9e6b66b354f8bc15 | 2026-01-23T00:00:00-05:00 | Distillation-based Layer Dropping (DLD) Effective End-to-end Framework for Dynamic Speech Networks | arXiv:2601.16117v1 Announce Type: new Abstract: Edge devices operate in constrained and varying resource settings, requiring dynamic architectures that can adapt to limitations of the available resources. To meet such demands, layer dropping ($\mathcal{LD}$) approach is typically used to transform static models into dy... | https://arxiv.org/abs/2601.16117 | Academic Papers | svg |
f9a5932022fcb8198c3707c7f07bae5cc40549f5d977671d0633b9ca24c28bd8 | 2026-01-23T00:00:00-05:00 | A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware | arXiv:2601.16118v1 Announce Type: new Abstract: Executing Spiking Neural Networks (SNNs) on neuromorphic hardware poses the problem of mapping neurons to cores. SNNs operate by propagating spikes between neurons that form a graph through synapses. Neuromorphic hardware mimics them through a network-on-chip, transmittin... | https://arxiv.org/abs/2601.16118 | Academic Papers | svg |
6cb71c85c8684c09aad8aad2a2b6aba3fad8e3db29ec702bee04c4bf1725499f | 2026-01-23T00:00:00-05:00 | Canonical structure of the LLG equation for exponential updates in micromagnetism | arXiv:2601.16122v1 Announce Type: new Abstract: In this contribution we propose an exponential update algorithm for magnetic moments appearing in the framework of micromagnetics and the Landau-Lifshitz-Gilbert (LLG) equation. This algorithm can be interpreted as the geometric integration on spheres, that a priori satis... | https://arxiv.org/abs/2601.16122 | Academic Papers | svg |
a983437146d461f4b216742252654e80986229caa04a7e14fb25bd1f89625ac1 | 2026-01-23T00:00:00-05:00 | A hybrid reconstruction of piece-wise smooth functions from non-uniform Fourier data | arXiv:2601.16124v1 Announce Type: new Abstract: In this paper, we consider the problem of reconstructing piece-wise smooth functions from their non-uniform Fourier data. We first extend the filter method for uniform Fourier data to the non-uniform setting by using the techniques of admissible frames. We show that the p... | https://arxiv.org/abs/2601.16124 | Academic Papers | svg |
77b003e9a799b691958356a7a6d11e3bee0058f9595472b06d611ba695a1d139 | 2026-01-23T00:00:00-05:00 | Rethinking Composed Image Retrieval Evaluation: A Fine-Grained Benchmark from Image Editing | arXiv:2601.16125v1 Announce Type: new Abstract: Composed Image Retrieval (CIR) is a pivotal and complex task in multimodal understanding. Current CIR benchmarks typically feature limited query categories and fail to capture the diverse requirements of real-world scenarios. To bridge this evaluation gap, we leverage ima... | https://arxiv.org/abs/2601.16125 | Academic Papers | svg |
9592d4da25b542a66020a91f520397af02faa9d25498069b03c921980fdd9cb0 | 2026-01-23T00:00:00-05:00 | Improving Training Efficiency and Reducing Maintenance Costs via Language Specific Model Merging | arXiv:2601.16127v1 Announce Type: new Abstract: Fine-tuning a task-specific multilingual large language model (LLM) involves training the model on a multilingual dataset with examples in all the required languages. Updating one or more supported languages with additional data or adding support for a new language involv... | https://arxiv.org/abs/2601.16127 | Academic Papers | svg |
93d6c5bac2b34d6aa6afc6659a91cd7d583b554031259b7c6d0e4025e31aceaa | 2026-01-23T00:00:00-05:00 | Replicating Human Motivated Reasoning Studies with LLMs | arXiv:2601.16130v1 Announce Type: new Abstract: Motivated reasoning -- the idea that individuals processing information may be motivated to reach a certain conclusion, whether it be accurate or predetermined -- has been well-explored as a human phenomenon. However, it is unclear whether base LLMs mimic these motivation... | https://arxiv.org/abs/2601.16130 | Academic Papers | svg |
7ec018b8de181e6856b149e27c36a271e44217b385683aefdf316492003c8434 | 2026-01-23T00:00:00-05:00 | LLM Prompt Evaluation for Educational Applications | arXiv:2601.16134v1 Announce Type: new Abstract: As large language models (LLMs) become increasingly common in educational applications, there is a growing need for evidence-based methods to design and evaluate LLM prompts that produce personalized and pedagogically aligned out-puts. This study presents a generalizable,... | https://arxiv.org/abs/2601.16134 | Academic Papers | svg |
a5253c66f3a2008f682fd4bcf4df88060e2302fa72d0e30c0217467f8f163b47 | 2026-01-23T00:00:00-05:00 | Automatic Classification of Arabic Literature into Historical Eras | arXiv:2601.16138v1 Announce Type: new Abstract: The Arabic language has undergone notable transformations over time, including the emergence of new vocabulary, the obsolescence of others, and shifts in word usage. This evolution is evident in the distinction between the classical and modern Arabic eras. Although histor... | https://arxiv.org/abs/2601.16138 | Academic Papers | svg |
583885e0e10fdd555bfbd31c058d671ad150d3d99bf5375fe5c6209802293b30 | 2026-01-23T00:00:00-05:00 | On the Intrinsic Dimensions of Data in Kernel Learning | arXiv:2601.16139v1 Announce Type: new Abstract: The manifold hypothesis suggests that the generalization performance of machine learning methods improves significantly when the intrinsic dimension of the input distribution's support is low. In the context of KRR, we investigate two alternative notions of intrinsic dime... | https://arxiv.org/abs/2601.16139 | Academic Papers | svg |
dec794c1a410daceb4d255533a922542123d4c6f6513695dd58b64bd60dcc465 | 2026-01-23T00:00:00-05:00 | Learning to Watermark in the Latent Space of Generative Models | arXiv:2601.16140v1 Announce Type: new Abstract: Existing approaches for watermarking AI-generated images often rely on post-hoc methods applied in pixel space, introducing computational overhead and potential visual artifacts. In this work, we explore latent space watermarking and introduce DistSeal, a unified approach... | https://arxiv.org/abs/2601.16140 | Academic Papers | svg |
f066ac9ec9dd3f461ecb0779eec7b88f3bef8b558d90f046b874ebb688105356 | 2026-01-23T00:00:00-05:00 | Computing Fixpoints of Learned Functions: Chaotic Iteration and Simple Stochastic Games | arXiv:2601.16142v1 Announce Type: new Abstract: The problem of determining the (least) fixpoint of (higher-dimensional) functions over the non-negative reals frequently occurs when dealing with systems endowed with a quantitative semantics. We focus on the situation in which the functions of interest are not known prec... | https://arxiv.org/abs/2601.16142 | Academic Papers | svg |
f4ea723f72f884e0bfafca71ff1639bf968f9b542bcf74a7ca5e30cb1982d6f7 | 2026-01-23T00:00:00-05:00 | Low-altitude Multi-UAV-assisted Data Collection and Semantic Forwarding for Post-Disaster Relief | arXiv:2601.16146v1 Announce Type: new Abstract: The low-altitude economy (LAE) is an emerging economic paradigm which fosters integrated development across multiple fields. As a pivotal component of the LAE, low-altitude uncrewed aerial vehicles (UAVs) can restore communication by serving as aerial relays between the p... | https://arxiv.org/abs/2601.16146 | Academic Papers | svg |
057ca155199877995e49a36c934a8f03ed21b0e9ebb5b8b59231286e33ac2e4d | 2026-01-23T00:00:00-05:00 | Beat-ssl: Capturing Local ECG Morphology through Heartbeat-level Contrastive Learning with Soft Targets | arXiv:2601.16147v1 Announce Type: new Abstract: Obtaining labelled ECG data for developing supervised models is challenging. Contrastive learning (CL) has emerged as a promising pretraining approach that enables effective transfer learning with limited labelled data. However, existing CL frameworks either focus solely ... | https://arxiv.org/abs/2601.16147 | Academic Papers | svg |
89eb213a5b344f45131650eb1ed6c72095f49d738ab2871d0e9c64bde4ae961a | 2026-01-23T00:00:00-05:00 | ActionMesh: Animated 3D Mesh Generation with Temporal 3D Diffusion | arXiv:2601.16148v1 Announce Type: new Abstract: Generating animated 3D objects is at the heart of many applications, yet most advanced works are typically difficult to apply in practice because of their limited setup, their long runtime, or their limited quality. We introduce ActionMesh, a generative model that predict... | https://arxiv.org/abs/2601.16148 | Academic Papers | svg |
fca88fb64b7ea5723f4bbaae854a822b7f2437555fbd184ef2cc316f35131664 | 2026-01-23T00:00:00-05:00 | Interconnection-based Model Reduction for Linear Hybrid Systems | arXiv:2601.16149v1 Announce Type: new Abstract: In this paper, we address the model reduction problem for linear hybrid systems via the interconnection-based technique called moment matching. We consider two classical interconnections, namely the direct and swapped interconnections, in the hybrid setting, and we presen... | https://arxiv.org/abs/2601.16149 | Academic Papers | svg |
72ac6799cd55f5451ba5ddd29b2be87ca4fd8aebd3da3534381ebc83f4dde151 | 2026-01-23T00:00:00-05:00 | Pay (Cross) Attention to the Melody: Curriculum Masking for Single-Encoder Melodic Harmonization | arXiv:2601.16150v1 Announce Type: new Abstract: Melodic harmonization, the task of generating harmonic accompaniments for a given melody, remains a central challenge in computational music generation. Recent single encoder transformer approaches have framed harmonization as a masked sequence modeling problem, but exist... | https://arxiv.org/abs/2601.16150 | Academic Papers | svg |
f929746cf3e9ed0ba0e25f239ee23660248990e7695d0ebc3cecafff664b4362 | 2026-01-23T00:00:00-05:00 | Substrate Stability Under Persistent Disagreement: Structural Constraints for Neutral Ontological Substrates | arXiv:2601.16152v1 Announce Type: new Abstract: Modern data systems increasingly operate under conditions of persistent legal, political, and analytic disagreement. In such settings, interoperability cannot rely on shared interpretation, negotiated semantics, or centralized authority. Instead, representations must func... | https://arxiv.org/abs/2601.16152 | Academic Papers | svg |
dd47a04f4b678c0e432dc6f8b9c7e55c499c763ffcfa98700d182bfc1b6faa97 | 2026-01-23T00:00:00-05:00 | HVD: Human Vision-Driven Video Representation Learning for Text-Video Retrieval | arXiv:2601.16155v1 Announce Type: new Abstract: The success of CLIP has driven substantial progress in text-video retrieval. However, current methods often suffer from "blind" feature interaction, where the model struggles to discern key visual information from background noise due to the sparsity of textual queries. T... | https://arxiv.org/abs/2601.16155 | Academic Papers | svg |
356c28f4a2cb110765e4168fd77ecf255d3cc5db72e8ad8aaf5556245058cfe7 | 2026-01-23T00:00:00-05:00 | All ascents exponential from valued constraint graphs of pathwidth three | arXiv:2601.16156v1 Announce Type: new Abstract: Many combinatorial optimization problems can be formulated as finding as assignment that maximized some pseudo-Boolean function (that we call the fitness function). Strict local search starts with some assignment and follows some update rule to proceed to an adjacent assi... | https://arxiv.org/abs/2601.16156 | Academic Papers | svg |
8a0166b7ad0858a04d8133ae3d7d26dca2ad0b36a41e73d6df6c358eb4daf3ea | 2026-01-23T00:00:00-05:00 | Domain-Incremental Continual Learning for Robust and Efficient Keyword Spotting in Resource Constrained Systems | arXiv:2601.16158v1 Announce Type: new Abstract: Keyword Spotting (KWS) systems with small footprint models deployed on edge devices face significant accuracy and robustness challenges due to domain shifts caused by varying noise and recording conditions. To address this, we propose a comprehensive framework for continu... | https://arxiv.org/abs/2601.16158 | Academic Papers | svg |
567eb50f154750825eaecec5122a585c144e28259d7b98d1f160f21cc2b300ea | 2026-01-23T00:00:00-05:00 | CONTEX-T: Contextual Privacy Exploitation via Transformer Spectral Analysis for IoT Device Fingerprinting | arXiv:2601.16160v1 Announce Type: new Abstract: The rapid expansion of internet of things (IoT) devices have created a pervasive ecosystem where encrypted wireless communications serve as the primary privacy and security protection mechanism. While encryption effectively protects message content, packet metadata and st... | https://arxiv.org/abs/2601.16160 | Academic Papers | svg |
712af5b019a6b1e70a663460637cf3ff3dba634791e81238bd1c63d4970d1039 | 2026-01-23T00:00:00-05:00 | Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning | arXiv:2601.16163v1 Announce Type: new Abstract: Recent video generation models demonstrate remarkable ability to capture complex physical interactions and scene evolution over time. To leverage their spatiotemporal priors, robotics works have adapted video models for policy learning but introduce complexity by requirin... | https://arxiv.org/abs/2601.16163 | Academic Papers | svg |
049557e2f50e52f56343afde7199091cbca3a87a1b91998278873710fc5eb728 | 2026-01-23T00:00:00-05:00 | Tensor Reed-Muller Codes: Achieving Capacity with Quasilinear Decoding Time | arXiv:2601.16164v1 Announce Type: new Abstract: Define the codewords of the Tensor Reed-Muller code $\mathsf{TRM}(r_1,m_1;r_2,m_2;\dots;r_t,m_t)$ to be the evaluation vectors of all multivariate polynomials in the variables $\left\{x_{ij}\right\}_{i=1,\dots,t}^{j=1,\dots m_i}$ with degree at most $r_i$ in the variables... | https://arxiv.org/abs/2601.16164 | Academic Papers | svg |
66f1db3914c3483d94b5f79111f5c07cdaaef655963f6021b91f039723cf75e3 | 2026-01-23T00:00:00-05:00 | Scaling Sample-Based Quantum Diagonalization on GPU-Accelerated Systems using OpenMP Offload | arXiv:2601.16169v1 Announce Type: new Abstract: Hybrid quantum-HPC algorithms advance research by delegating complex tasks to quantum processors and using HPC systems to orchestrate workflows and complementary computations. Sample-based quantum diagonalization (SQD) is a hybrid quantum-HPC method in which information f... | https://arxiv.org/abs/2601.16169 | Academic Papers | svg |
de7d255547a2d012e486a4e56cc269bf6fc7dbfba57661c31ca66b40f26e7f81 | 2026-01-23T00:00:00-05:00 | Non-Linearly Separable Distributed Computing: A Sparse Tensor Factorization Approach | arXiv:2601.16171v1 Announce Type: new Abstract: The work considers the $N$-server distributed computing setting with $K$ users requesting functions that are arbitrary multi-variable polynomial evaluations of $L$ real (potentially non-linear) basis subfunctions. Our aim is to seek efficient task-allocation and data-comm... | https://arxiv.org/abs/2601.16171 | Academic Papers | svg |
6ca5e1a5143ceaf3f79426351389a78c35600c3e20c3820af9d015b260658036 | 2026-01-23T00:00:00-05:00 | Structured Hints for Sample-Efficient Lean Theorem Proving | arXiv:2601.16172v1 Announce Type: new Abstract: State-of-the-art neural theorem provers like DeepSeek-Prover-V1.5 combine large language models with reinforcement learning, achieving impressive results through sophisticated training. We ask: do these highly-trained models still benefit from simple structural guidance a... | https://arxiv.org/abs/2601.16172 | Academic Papers | svg |
d907959c4301eb0cad56e811cfc674d34d8e7c57847fcbc77a3c22ff9ac606a8 | 2026-01-23T00:00:00-05:00 | Learning to Discover at Test Time | arXiv:2601.16175v1 Announce Type: new Abstract: How can we use AI to discover a new state of the art for a scientific problem? Prior work in test-time scaling, such as AlphaEvolve, performs search by prompting a frozen LLM. We perform reinforcement learning at test time, so the LLM can continue to train, but now with e... | https://arxiv.org/abs/2601.16175 | Academic Papers | svg |
a0c090e4731e500fb6b20b4e174f8f2e3bfb2926cc212fb332e7ddc1a3f425a8 | 2026-01-23T00:00:00-05:00 | Dynamic Pattern Matching with Wildcards | arXiv:2601.16182v1 Announce Type: new Abstract: We study the fully dynamic pattern matching problem where the pattern may contain up to kwildcard symbols, each matching any symbol of the alphabet. Both the text and the pattern are subject to updates (insert, delete, change). We design an algorithm with O(nlog^2 n) prep... | https://arxiv.org/abs/2601.16182 | Academic Papers | svg |
b46c146af951bab32debb0c24c7af87012209e5625e1917e0e9ad610f86bff49 | 2026-01-23T00:00:00-05:00 | Average Unfairness in Routing Games | arXiv:2601.16187v1 Announce Type: new Abstract: We propose average unfairness as a new measure of fairness in routing games, defined as the ratio between the average latency and the minimum latency experienced by users. This measure is a natural complement to two existing unfairness notions: loaded unfairness, which co... | https://arxiv.org/abs/2601.16187 | Academic Papers | svg |
d391f3b4b09fd6a68cbc267d00ea3049f755e9fe86eb001f46a70ca98d38f8ad | 2026-01-23T00:00:00-05:00 | 360Anything: Geometry-Free Lifting of Images and Videos to 360{\deg} | arXiv:2601.16192v1 Announce Type: new Abstract: Lifting perspective images and videos to 360{\deg} panoramas enables immersive 3D world generation. Existing approaches often rely on explicit geometric alignment between the perspective and the equirectangular projection (ERP) space. Yet, this requires known camera metad... | https://arxiv.org/abs/2601.16192 | Academic Papers | svg |
f3331dc209ca5e908ae3b033faaaca09c4c861495fdbea2607a62a97bfae0929 | 2026-01-23T00:00:00-05:00 | Stochastic Control Barrier Functions under State Estimation: From Euclidean Space to Lie Groups | arXiv:2601.16198v1 Announce Type: new Abstract: Ensuring safety for autonomous systems under uncertainty remains challenging, particularly when safety of the true state is required despite the true state not being fully known. Control barrier functions (CBFs) have become widely adopted as safety filters. However, stand... | https://arxiv.org/abs/2601.16198 | Academic Papers | svg |
9d6a2066d701584331cd48ae3b9782b0d71045341733a9616697afcdd2897be7 | 2026-01-23T00:00:00-05:00 | PAL*M: Property Attestation for Large Generative Models | arXiv:2601.16199v1 Announce Type: new Abstract: Machine learning property attestations allow provers (e.g., model providers or owners) to attest properties of their models/datasets to verifiers (e.g., regulators, customers), enabling accountability towards regulations and policies. But, current approaches do not suppor... | https://arxiv.org/abs/2601.16199 | Academic Papers | svg |
b3a0bec00eb019feb7ba90e491108e8f37359a4186275a3e8054a74122068f18 | 2026-01-23T00:00:00-05:00 | Provable Robustness in Multimodal Large Language Models via Feature Space Smoothing | arXiv:2601.16200v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) exhibit strong capabilities across diverse applications, yet remain vulnerable to adversarial perturbations that distort their feature representations and induce erroneous predictions. To address this vulnerability, we propose the ... | https://arxiv.org/abs/2601.16200 | Academic Papers | svg |
6a58255400c8ee5f4173ac5e349405ac22a3f09875d0cfd046092585e746a0e1 | 2026-01-23T00:00:00-05:00 | Counterfactual Training: Teaching Models Plausible and Actionable Explanations | arXiv:2601.16205v1 Announce Type: new Abstract: We propose a novel training regime termed counterfactual training that leverages counterfactual explanations to increase the explanatory capacity of models. Counterfactual explanations have emerged as a popular post-hoc explanation method for opaque machine learning model... | https://arxiv.org/abs/2601.16205 | Academic Papers | svg |
870fcd263ef7e48d85834d97d30db82a1b556cafbfb2ac5814264f4d5229d50e | 2026-01-23T00:00:00-05:00 | LLM-in-Sandbox Elicits General Agentic Intelligence | arXiv:2601.16206v1 Announce Type: new Abstract: We introduce LLM-in-Sandbox, enabling LLMs to explore within a code sandbox (i.e., a virtual computer), to elicit general intelligence in non-code domains. We first demonstrate that strong LLMs, without additional training, exhibit generalization capabilities to leverage ... | https://arxiv.org/abs/2601.16206 | Academic Papers | svg |
f1d63e90befa82ad5b1b1be9c986f3665f44aef6655b84f26c5107201d7accb8 | 2026-01-23T00:00:00-05:00 | IVRA: Improving Visual-Token Relations for Robot Action Policy with Training-Free Hint-Based Guidance | arXiv:2601.16207v1 Announce Type: new Abstract: Many Vision-Language-Action (VLA) models flatten image patches into a 1D token sequence, weakening the 2D spatial cues needed for precise manipulation. We introduce IVRA, a lightweight, training-free method that improves spatial understanding by exploiting affinity hints ... | https://arxiv.org/abs/2601.16207 | Academic Papers | svg |
465786db3830ba4836aba6c7e6407eeed70da6680113b304a6e2fa6b35a318e2 | 2026-01-23T00:00:00-05:00 | Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders | arXiv:2601.16208v1 Announce Type: new Abstract: Representation Autoencoders (RAEs) have shown distinct advantages in diffusion modeling on ImageNet by training in high-dimensional semantic latent spaces. In this work, we investigate whether this framework can scale to large-scale, freeform text-to-image (T2I) generatio... | https://arxiv.org/abs/2601.16208 | Academic Papers | svg |
f3913e3ff42e99d63e5084e6e5e406c989cf245a3cb6f3dda18edf61558927bc | 2026-01-23T00:00:00-05:00 | PyraTok: Language-Aligned Pyramidal Tokenizer for Video Understanding and Generation | arXiv:2601.16210v1 Announce Type: new Abstract: Discrete video VAEs underpin modern text-to-video generation and video understanding systems, yet existing tokenizers typically learn visual codebooks at a single scale with limited vocabularies and shallow language supervision, leading to poor cross-modal alignment and z... | https://arxiv.org/abs/2601.16210 | Academic Papers | svg |
75d5f38f0fdf6cb7bdd67ba8cff65448afa6a7854cdc365ef786cdab79c337e5 | 2026-01-23T00:00:00-05:00 | Why Can't I Open My Drawer? Mitigating Object-Driven Shortcuts in Zero-Shot Compositional Action Recognition | arXiv:2601.16211v1 Announce Type: new Abstract: We study Compositional Video Understanding (CVU), where models must recognize verbs and objects and compose them to generalize to unseen combinations. We find that existing Zero-Shot Compositional Action Recognition (ZS-CAR) models fail primarily due to an overlooked fail... | https://arxiv.org/abs/2601.16211 | Academic Papers | svg |
4945d13a9d1986aa5f07f94f1a919c4ed8f5cffcbc1f9f071e3d360603b9f877 | 2026-01-23T00:00:00-05:00 | Point Bridge: 3D Representations for Cross Domain Policy Learning | arXiv:2601.16212v1 Announce Type: new Abstract: Robot foundation models are beginning to deliver on the promise of generalist robotic agents, yet progress remains constrained by the scarcity of large-scale real-world manipulation datasets. Simulation and synthetic data generation offer a scalable alternative, but their... | https://arxiv.org/abs/2601.16212 | Academic Papers | svg |
e772bbd23ae442d040f1dd22646b62276bf6d559de4caf071f4c552cfcd0ac3e | 2026-01-23T00:00:00-05:00 | CamPilot: Improving Camera Control in Video Diffusion Model with Efficient Camera Reward Feedback | arXiv:2601.16214v1 Announce Type: new Abstract: Recent advances in camera-controlled video diffusion models have significantly improved video-camera alignment. However, the camera controllability still remains limited. In this work, we build upon Reward Feedback Learning and aim to further improve camera controllabilit... | https://arxiv.org/abs/2601.16214 | Academic Papers | svg |
ecb517eb0f6faa42968e322b0d4e2095523ff13e236061a72420a10bd78f3918 | 2026-01-23T00:00:00-05:00 | Scalable Board Expansion within a General Game System | arXiv:2601.16216v1 Announce Type: new Abstract: This thesis explores the use of a General Game System (GGS) to support the automatic expansion of game boards in boardless games. Traditional implementations of such games often rely on oversized static boards defined from the start, even though large portions of these bo... | https://arxiv.org/abs/2601.16216 | Academic Papers | svg |
4855b8571ff2ceff25fdfe7b551939aeb187f56409aebe271f6c78d5c3ee01e1 | 2026-01-23T00:00:00-05:00 | Real-Time HAP-Assisted Vehicular Edge Computing for Rural Areas | arXiv:2301.09957v1 Announce Type: cross Abstract: Non-Terrestrial Networks (NTNs) are expected to be a key component of 6th generation (6G) networks to support broadband seamless Internet connectivity and expand the coverage even in rural and remote areas. In this context, High Altitude Platforms (HAPs) can act as edge... | https://arxiv.org/abs/2301.09957 | Academic Papers | svg |
3340227a8bcf8ba01d15ee98a394279f09492f295660e881d2e871c5e1afb5bd | 2026-01-23T00:00:00-05:00 | Performance Evaluation of LoRa for IoT Applications in Non-Terrestrial Networks via ns-3 | arXiv:2509.02811v1 Announce Type: cross Abstract: The integration of Internet of Things (IoT) and Non-Terrestrial Networks (NTNs) has emerged as a key paradigm to provide connectivity for sensors and actuators via satellite gateways in remote areas where terrestrial infrastructure is limited or unavailable. Among other... | https://arxiv.org/abs/2509.02811 | Academic Papers | svg |
ed416eb0185af9b215a502c55aadadb745626d473a4740d87c4642bbeaa3579a | 2026-01-23T00:00:00-05:00 | Psychometric Comparability of LLM-Based Digital Twins | arXiv:2601.14264v1 Announce Type: cross Abstract: Large language models (LLMs) are used as "digital twins" to replace human respondents, yet their psychometric comparability to humans is uncertain. We propose a construct-validity framework spanning construct representation and the nomological net, benchmarking digital ... | https://arxiv.org/abs/2601.14264 | Academic Papers | svg |
cd1f676c86eab105a5cdd796a9e0fa99b6919ea50d77e1cc3c16bfc17b6749de | 2026-01-23T00:00:00-05:00 | 5G NR Non-Terrestrial Networks: Open Challenges for Full-Stack Protocol Design | arXiv:2601.14883v1 Announce Type: cross Abstract: As 5th generation (5G) networks continue to evolve, there is a growing interest toward the integration of Terrestrial Networks (TNs) and Non-Terrestrial Networks (NTNs). Specifically, NTNs leverage space/air base stations such as satellites, High Altitude Platforms (HAP... | https://arxiv.org/abs/2601.14883 | Academic Papers | svg |
93a13a9d7d58e3ced96d5874b47afbb4437aa420662263132444eb7bcbb6b30d | 2026-01-23T00:00:00-05:00 | Knowledge Graphs are Implicit Reward Models: Path-Derived Signals Enable Compositional Reasoning | arXiv:2601.15160v1 Announce Type: cross Abstract: Large language models have achieved near-expert performance in structured reasoning domains like mathematics and programming, yet their ability to perform compositional multi-hop reasoning in specialized scientific fields remains limited. We propose a bottom-up learning... | https://arxiv.org/abs/2601.15160 | Academic Papers | svg |
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