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e68b69cced767d031294986b436e87c753cb395203b291d938bb961aa3fd9fef | 2026-01-16T00:00:00-05:00 | Algebraic Properties of PAC Codes | arXiv:2601.10262v1 Announce Type: new Abstract: We analyze polarization-adjusted convolutional codes using the algebraic representation of polar and Reed-Muller codes. We define a large class of codes, called generalized polynomial polar codes which include PAC codes and Reverse PAC codes. We derive structural properti... | https://arxiv.org/abs/2601.10262 | Academic Papers | svg |
3d61eab9f7b10e9366280f3652845f09613004490293b31306510070e3766300 | 2026-01-16T00:00:00-05:00 | An Ensemble of Evolutionary Algorithms With Both Crisscross Search and Sparrow Search for Processing Inferior Individuals | arXiv:2601.10263v1 Announce Type: new Abstract: In the field of artificial intelligence, real parameter single objective optimization is an important direction. Both the Differential Evolution (DE) and the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) demonstrate good performance for real parameter single ob... | https://arxiv.org/abs/2601.10263 | Academic Papers | svg |
0a284f6c14e36dccd01b6a4ccac9a178f3059f67ecc70c3525498f876ca87599 | 2026-01-16T00:00:00-05:00 | Measuring Affinity between Attention-Head Weight Subspaces via the Projection Kernel | arXiv:2601.10266v1 Announce Type: new Abstract: Understanding relationships between attention heads is essential for interpreting the internal structure of Transformers, yet existing metrics do not capture this structure well. We focus on the subspaces spanned by attention-head weight matrices and quantify head-to-head... | https://arxiv.org/abs/2601.10266 | Academic Papers | svg |
b686c28c48b513d889b3e7c8e73a7bdc6a5917c0ef6a628bd16f0a55905dbd8c | 2026-01-16T00:00:00-05:00 | In-Context Source and Channel Coding | arXiv:2601.10267v1 Announce Type: new Abstract: Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders and powerful channel codes. However, SSCC often suffers from a pronounced cliff effect in low Signal-to-Noise Ratio (SNR) regi... | https://arxiv.org/abs/2601.10267 | Academic Papers | svg |
b1a7f4ae629b4b78f6cb8d54d8024a615ba1b853bc0bcd3bc8f5221265fa149d | 2026-01-16T00:00:00-05:00 | The impact of tactile sensor configurations on grasp learning efficiency -- a comparative evaluation in simulation | arXiv:2601.10268v1 Announce Type: new Abstract: Tactile sensors are breaking into the field of robotics to provide direct information related to contact surfaces, including contact events, slip events and even texture identification. These events are especially important for robotic hand designs, including prosthetics,... | https://arxiv.org/abs/2601.10268 | Academic Papers | svg |
75576564470364e0eaf12b1e99e0f1229f366b43f730db81510e964a8af761d3 | 2026-01-16T00:00:00-05:00 | Early Fault Detection on CMAPSS with Unsupervised LSTM Autoencoders | arXiv:2601.10269v1 Announce Type: new Abstract: This paper introduces an unsupervised health-monitoring framework for turbofan engines that does not require run-to-failure labels. First, operating-condition effects in NASA CMAPSS sensor streams are removed via regression-based normalisation; then a Long Short-Term Memo... | https://arxiv.org/abs/2601.10269 | Academic Papers | svg |
f69c874c62ba140d863e853bd8d7018ef1f200509fc0fc858dde6759c49e8dff | 2026-01-16T00:00:00-05:00 | MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts | arXiv:2601.10272v1 Announce Type: new Abstract: We present MoST (Mixture of Speech and Text), a novel multimodal large language model that seamlessly integrates speech and text processing through our proposed Modality-Aware Mixture of Experts (MAMoE) architecture. While current multimodal models typically process diver... | https://arxiv.org/abs/2601.10272 | Academic Papers | svg |
048dd4ec9784631633264d383ce01c05b6e2bef3edc5e511e619125be169e873 | 2026-01-16T00:00:00-05:00 | Queueing-Aware Optimization of Reasoning Tokens for Accuracy-Latency Trade-offs in LLM Servers | arXiv:2601.10274v1 Announce Type: new Abstract: We consider a single large language model (LLM) server that serves a heterogeneous stream of queries belonging to $N$ distinct task types. Queries arrive according to a Poisson process, and each type occurs with a known prior probability. For each task type, the server al... | https://arxiv.org/abs/2601.10274 | Academic Papers | svg |
00518351c26ee268e80489f44cf30c821a99dcc597e986df615ca0e7043cc70d | 2026-01-16T00:00:00-05:00 | SCRamble: Adaptive Decentralized Overlay Construction for Blockchain Networks | arXiv:2601.10277v1 Announce Type: new Abstract: Despite being under development for over 15 years, transaction throughput remains one of the key challenges confronting blockchains, which typically has a cap of a limited number of transactions per second. A fundamental factor limiting this metric is the network latency ... | https://arxiv.org/abs/2601.10277 | Academic Papers | svg |
c85f34e5a582d335965d94468460b2fffca736cc2ac81f4a53f50f1bfd1e88cf | 2026-01-16T00:00:00-05:00 | SPIKE: Sparse Koopman Regularization for Physics-Informed Neural Networks | arXiv:2601.10282v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) provide a mesh-free approach for solving differential equations by embedding physical constraints into neural network training. However, PINNs tend to overfit within the training domain, leading to poor generalization when extrapol... | https://arxiv.org/abs/2601.10282 | Academic Papers | svg |
3372133f99e9abc0d0ee39e0f0434a19bc83ba6433bf1e80374a0e6482a2afc7 | 2026-01-16T00:00:00-05:00 | Atelier \`a la conf\'erence IHM 2025 : RA Permanente | arXiv:2601.10291v1 Announce Type: new Abstract: As we move towards more ubiquitous computing, the concept of pervasive augmented reality (PAR) could lead to a major evolution in the relationship between humans, computing and the world. The experience of a continuously augmented world can have both benefits and undesira... | https://arxiv.org/abs/2601.10291 | Academic Papers | svg |
05a1ccaebb4d2fcba056a09b9749d2760c98dd5456ef509454df77daf8478388 | 2026-01-16T00:00:00-05:00 | Single-Feed Circularly Polarized Super Realized Gain Antenna | arXiv:2601.10292v1 Announce Type: new Abstract: This paper presents a super realized gain, circularly polarized strip-crossed dipole antenna operating at 3.5 GHz. Superdirective behavior is achieved by leveraging strong inter-element mutual coupling through careful adjustment of the strip dimensions. The antenna featur... | https://arxiv.org/abs/2601.10292 | Academic Papers | svg |
98d96fa91665194317075e9f0720df49e9fe1d9b8692bda7ef9e131de1acfb09 | 2026-01-16T00:00:00-05:00 | Reasoning Hijacking: Subverting LLM Classification via Decision-Criteria Injection | arXiv:2601.10294v1 Announce Type: new Abstract: Current LLM safety research predominantly focuses on mitigating Goal Hijacking, preventing attackers from redirecting a model's high-level objective (e.g., from "summarizing emails" to "phishing users"). In this paper, we argue that this perspective is incomplete and high... | https://arxiv.org/abs/2601.10294 | Academic Papers | svg |
054e56d17cc45f409d9b84dbc9e510c07cfc5b02a19a81015ffce96da7291738 | 2026-01-16T00:00:00-05:00 | Multipath Routing for Multi-Hop UAV Networks | arXiv:2601.10299v1 Announce Type: new Abstract: Multi-hop uncrewed aerial vehicle (UAV) networks are promising to extend the terrestrial network coverage. Existing multi-hop UAV networks employ a single routing path by selecting the next-hop forwarding node in a hop-by-hop manner, which leads to local congestion and in... | https://arxiv.org/abs/2601.10299 | Academic Papers | svg |
6c1a8610c629a47a8210e146fbee72ce1c1824939f8719490e825de9f0c0dd0d | 2026-01-16T00:00:00-05:00 | DanQing: An Up-to-Date Large-Scale Chinese Vision-Language Pre-training Dataset | arXiv:2601.10305v1 Announce Type: new Abstract: Vision-Language Pre-training (VLP) models demonstrate strong performance across various downstream tasks by learning from large-scale image-text pairs through contrastive pretraining. The release of extensive English image-text datasets (e.g., COYO-700M and LAION-400M) ha... | https://arxiv.org/abs/2601.10305 | Academic Papers | svg |
8b35a3cfac9fc2b2b249149a05735ef0afb0536e2dc90dfc903839d7dc8dfdda | 2026-01-16T00:00:00-05:00 | Evidence-Augmented Policy Optimization with Reward Co-Evolution for Long-Context Reasoning | arXiv:2601.10306v1 Announce Type: new Abstract: While Reinforcement Learning (RL) has advanced LLM reasoning, applying it to long-context scenarios is hindered by sparsity of outcome rewards. This limitation fails to penalize ungrounded "lucky guesses," leaving the critical process of needle-in-a-haystack evidence retr... | https://arxiv.org/abs/2601.10306 | Academic Papers | svg |
b16317cf255e42df6a33a29db459faaa7f112e6e0188a335cddf215a3885ada3 | 2026-01-16T00:00:00-05:00 | The Straight and Narrow: Do LLMs Possess an Internal Moral Path? | arXiv:2601.10307v1 Announce Type: new Abstract: Enhancing the moral alignment of Large Language Models (LLMs) is a critical challenge in AI safety. Current alignment techniques often act as superficial guardrails, leaving the intrinsic moral representations of LLMs largely untouched. In this paper, we bridge this gap b... | https://arxiv.org/abs/2601.10307 | Academic Papers | svg |
782534b8b1d1688d49c840e91bb78758bff51b2099364c5c8df829643c9ca7cb | 2026-01-16T00:00:00-05:00 | Multilinguality as Sense Adaptation | arXiv:2601.10310v1 Announce Type: new Abstract: We approach multilinguality as sense adaptation: aligning latent meaning representations across languages rather than relying solely on shared parameters and scale. In this paper, we introduce SENse-based Symmetric Interlingual Alignment (SENSIA), which adapts a Backpack ... | https://arxiv.org/abs/2601.10310 | Academic Papers | svg |
bc72c2b0ed7c20ff506a2f8b21f509a7cba727f5525a9f09727bceeb07ebcd27 | 2026-01-16T00:00:00-05:00 | We Need a More Robust Classifier: Dual Causal Learning Empowers Domain-Incremental Time Series Classification | arXiv:2601.10312v1 Announce Type: new Abstract: The World Wide Web thrives on intelligent services that rely on accurate time series classification, which has recently witnessed significant progress driven by advances in deep learning. However, existing studies face challenges in domain incremental learning. In this pa... | https://arxiv.org/abs/2601.10312 | Academic Papers | svg |
6ed82571e3a3a9c2d2470b123158cb6c3564409bc31ab2eb5c280ef2798c5f84 | 2026-01-16T00:00:00-05:00 | Hierarchical Refinement of Universal Multimodal Attacks on Vision-Language Models | arXiv:2601.10313v1 Announce Type: new Abstract: Existing adversarial attacks for VLP models are mostly sample-specific, resulting in substantial computational overhead when scaled to large datasets or new scenarios. To overcome this limitation, we propose Hierarchical Refinement Attack (HRA), a multimodal universal att... | https://arxiv.org/abs/2601.10313 | Academic Papers | svg |
c4b13b4004e34b5604ce2dca86a8657390641a3f95673094163bba6dee5a5eaf | 2026-01-16T00:00:00-05:00 | ADVOSYNTH: A Synthetic Multi-Advocate Dataset for Speaker Identification in Courtroom Scenarios | arXiv:2601.10315v1 Announce Type: new Abstract: As large-scale speech-to-speech models achieve high fidelity, the distinction between synthetic voices in structured environments becomes a vital area of study. This paper introduces Advosynth-500, a specialized dataset comprising 100 synthetic speech files featuring 10 u... | https://arxiv.org/abs/2601.10315 | Academic Papers | svg |
49393a4c1d6271d15b7fd1ad7004850e95e89f1812d08bf33b86369255471783 | 2026-01-16T00:00:00-05:00 | Boundary-Aware NL2SQL: Integrating Reliability through Hybrid Reward and Data Synthesis | arXiv:2601.10318v1 Announce Type: new Abstract: In this paper, we present BAR-SQL (Boundary-Aware Reliable NL2SQL), a unified training framework that embeds reliability and boundary awareness directly into the generation process. We introduce a Seed Mutation data synthesis paradigm that constructs a representative ente... | https://arxiv.org/abs/2601.10318 | Academic Papers | svg |
e13f4a4d49325d16ce1a4632da65462c041e1cd742cd51ff0c37142400acd45c | 2026-01-16T00:00:00-05:00 | An Efficient Long-Context Ranking Architecture With Calibrated LLM Distillation: Application to Person-Job Fit | arXiv:2601.10321v1 Announce Type: new Abstract: Finding the most relevant person for a job proposal in real time is challenging, especially when resumes are long, structured, and multilingual. In this paper, we propose a re-ranking model based on a new generation of late cross-attention architecture, that decomposes bo... | https://arxiv.org/abs/2601.10321 | Academic Papers | svg |
d791952cc4baf595de77a596270ab98660632ca9f160691bd7b2a28761cd1e49 | 2026-01-16T00:00:00-05:00 | Conjugate Gradient Methods are Not Efficient: Experimental Study of the Locality Limitation | arXiv:2601.10322v1 Announce Type: new Abstract: The convergence of the Conjugate Gradient method is subject to a locality limitation which imposes a lower bound on the number of iterations required before a qualitatively accurate approximation can be obtained. This limitation originates from the restricted transport of... | https://arxiv.org/abs/2601.10322 | Academic Papers | svg |
a957428b8cde9785ce9bb88afa5419f51be787f156ba2efac10813df1bd8b7c3 | 2026-01-16T00:00:00-05:00 | ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding | arXiv:2601.10323v1 Announce Type: new Abstract: Recent Omni-multimodal Large Language Models show promise in unified audio, vision, and text modeling. However, streaming audio-video understanding remains challenging, as existing approaches suffer from disjointed capabilities: they typically exhibit incomplete modality ... | https://arxiv.org/abs/2601.10323 | Academic Papers | svg |
e3f8f8c1115d15926fe2eaf19f0a692c3c3085fa1c138d1d3589247e274b74b7 | 2026-01-16T00:00:00-05:00 | SRAW-Attack: Space-Reweighted Adversarial Warping Attack for SAR Target Recognition | arXiv:2601.10324v1 Announce Type: new Abstract: Synthetic aperture radar (SAR) imagery exhibits intrinsic information sparsity due to its unique electromagnetic scattering mechanism. Despite the widespread adoption of deep neural network (DNN)-based SAR automatic target recognition (SAR-ATR) systems, they remain vulner... | https://arxiv.org/abs/2601.10324 | Academic Papers | svg |
3f75f28e2ed02a3f34d64a359557f5731ea227e9310289e8a9ebafe0aefe2bc8 | 2026-01-16T00:00:00-05:00 | Meta Dynamic Graph for Traffic Flow Prediction | arXiv:2601.10328v1 Announce Type: new Abstract: Traffic flow prediction is a typical spatio-temporal prediction problem and has a wide range of applications. The core challenge lies in modeling the underlying complex spatio-temporal dependencies. Various methods have been proposed, and recent studies show that the mode... | https://arxiv.org/abs/2601.10328 | Academic Papers | svg |
622823c1dfe3ea806becb4567bef3b5418ff08cd36a3b8e5709968231e4cd475 | 2026-01-16T00:00:00-05:00 | On the Capacity of Noisy Frequency-based Channels | arXiv:2601.10329v1 Announce Type: new Abstract: We investigate the capacity of noisy frequency-based channels, motivated by DNA data storage in the short-molecule regime, where information is encoded in the frequency of items types rather than their order. The channel output is a histogram formed by random sampling of ... | https://arxiv.org/abs/2601.10329 | Academic Papers | svg |
0d94bc340af02d347927f024173d123d48a71430314b72dd12232fa59ec4d941 | 2026-01-16T00:00:00-05:00 | Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders | arXiv:2601.10332v1 Announce Type: new Abstract: Recent progress in text-to-image (T2I) diffusion models (DMs) has enabled high-quality visual synthesis from diverse textual prompts. Yet, most existing T2I DMs, even those equipped with large language model (LLM)-based text encoders, remain text-pixel mappers -- they emp... | https://arxiv.org/abs/2601.10332 | Academic Papers | svg |
de5a550dcf0e7be8f3f8e9fd6825b34d6c1e2d9783f935a8f8cc8f986c5b6fa4 | 2026-01-16T00:00:00-05:00 | An analytic theory of convolutional neural network inverse problems solvers | arXiv:2601.10334v1 Announce Type: new Abstract: Supervised convolutional neural networks (CNNs) are widely used to solve imaging inverse problems, achieving state-of-the-art performance in numerous applications. However, despite their empirical success, these methods are poorly understood from a theoretical perspective... | https://arxiv.org/abs/2601.10334 | Academic Papers | svg |
37b024195b93ca088669add48159b32bb816ee6b68e736742400373ed45d348b | 2026-01-16T00:00:00-05:00 | Agent Skills in the Wild: An Empirical Study of Security Vulnerabilities at Scale | arXiv:2601.10338v1 Announce Type: new Abstract: The rise of AI agent frameworks has introduced agent skills, modular packages containing instructions and executable code that dynamically extend agent capabilities. While this architecture enables powerful customization, skills execute with implicit trust and minimal vet... | https://arxiv.org/abs/2601.10338 | Academic Papers | svg |
3bfe7743176c02b0cbeffbae3e2d6d7c4f3b50f10f5e5c697790271cd3e74f5d | 2026-01-16T00:00:00-05:00 | CHORAL: Traversal-Aware Planning for Safe and Efficient Heterogeneous Multi-Robot Routing | arXiv:2601.10340v1 Announce Type: new Abstract: Monitoring large, unknown, and complex environments with autonomous robots poses significant navigation challenges, where deploying teams of heterogeneous robots with complementary capabilities can substantially improve both mission performance and feasibility. However, e... | https://arxiv.org/abs/2601.10340 | Academic Papers | svg |
e68bdc5b1e3d6230e984bc46958f8fc1b254074cecb817436759b500876aa556 | 2026-01-16T00:00:00-05:00 | Convertible Codes for Data and Device Heterogeneity | arXiv:2601.10341v1 Announce Type: new Abstract: Distributed storage systems must handle both data heterogeneity, arising from non-uniform access demands, and device heterogeneity, caused by time-varying node reliability. In this paper, we study convertible codes, which enable the transformation of one code into another... | https://arxiv.org/abs/2601.10341 | Academic Papers | svg |
96f46ed323b2b160c9e34291160a12550190705929b6b97902950313dac5aec6 | 2026-01-16T00:00:00-05:00 | C-GRASP: Clinically-Grounded Reasoning for Affective Signal Processing | arXiv:2601.10342v1 Announce Type: new Abstract: Heart rate variability (HRV) is a pivotal noninvasive marker for autonomic monitoring; however, applying Large Language Models (LLMs) to HRV interpretation is hindered by physiological hallucinations. These include respiratory sinus arrhythmia (RSA) contamination, short-d... | https://arxiv.org/abs/2601.10342 | Academic Papers | svg |
a0619e10d8996a8cc52328966267406f4246aa060c6bba3d3a9acdcb7ccb68fc | 2026-01-16T00:00:00-05:00 | OctoBench: Benchmarking Scaffold-Aware Instruction Following in Repository-Grounded Agentic Coding | arXiv:2601.10343v1 Announce Type: new Abstract: Modern coding scaffolds turn LLMs into capable software agents, but their ability to follow scaffold-specified instructions remains under-examined, especially when constraints are heterogeneous and persist across interactions. To fill this gap, we introduce OctoBench, whi... | https://arxiv.org/abs/2601.10343 | Academic Papers | svg |
5b206a60b6bbe5d7ef509f3e9a63e2ac7b976520c677da3f11dabd8e8b0f6206 | 2026-01-16T00:00:00-05:00 | Self-supervised restoration of singing voice degraded by pitch shifting using shallow diffusion | arXiv:2601.10345v1 Announce Type: new Abstract: Pitch shifting has been an essential feature in singing voice production. However, conventional signal processing approaches exhibit well known trade offs such as formant shifts and robotic coloration that becomes more severe at larger transposition jumps. This paper targ... | https://arxiv.org/abs/2601.10345 | Academic Papers | svg |
7c41b1c2524c810da6a342301ce9b7d4dd87ed39779fc00f32a8e7fb6d429f35 | 2026-01-16T00:00:00-05:00 | Training-Trajectory-Aware Token Selection | arXiv:2601.10348v1 Announce Type: new Abstract: Efficient distillation is a key pathway for converting expensive reasoning capability into deployable efficiency, yet in the frontier regime where the student already has strong reasoning ability, naive continual distillation often yields limited gains or even degradation... | https://arxiv.org/abs/2601.10348 | Academic Papers | svg |
66df01452bec7dc85e6096547fd1524cdf75e303702d603fe264d6fee5c8870b | 2026-01-16T00:00:00-05:00 | SuS: Strategy-aware Surprise for Intrinsic Exploration | arXiv:2601.10349v1 Announce Type: new Abstract: We propose Strategy-aware Surprise (SuS), a novel intrinsic motivation framework that uses pre-post prediction mismatch as a novelty signal for exploration in reinforcement learning. Unlike traditional curiosity-driven methods that rely solely on state prediction error, S... | https://arxiv.org/abs/2601.10349 | Academic Papers | svg |
25c7bd7cf8785fe0774112e0af27604946415cde9436e8eb0903f5b779806b21 | 2026-01-16T00:00:00-05:00 | A New Construction Structure on MISO Coded Caching with Linear Subpacketization: Half-Sum Disjoint Packing | arXiv:2601.10353v1 Announce Type: new Abstract: In the $(L,K,M,N)$ cache-aided multiple-input single-output (MISO) broadcast channel (BC) system, the server is equipped with $L$ antennas and communicates with $K$ single-antenna users through a wireless broadcast channel where the server has a library containing $N$ fil... | https://arxiv.org/abs/2601.10353 | Academic Papers | svg |
34639b059cbf3195fb723715fbf05082328f9ba2c25457a905321cf77fed6ec7 | 2026-01-16T00:00:00-05:00 | Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text | arXiv:2601.10355v1 Announce Type: new Abstract: Enabling Large Language Models (LLMs) to effectively utilize tools in multi-turn interactions is essential for building capable autonomous agents. However, acquiring diverse and realistic multi-turn tool-use data remains a significant challenge. In this work, we propose a... | https://arxiv.org/abs/2601.10355 | Academic Papers | svg |
1dae375d2d6bcc47f4852b38bc4ebf495ae608bc2e888aae74f8ad7c7266d419 | 2026-01-16T00:00:00-05:00 | EvoMorph: Counterfactual Explanations for Continuous Time-Series Extrinsic Regression Applied to Photoplethysmography | arXiv:2601.10356v1 Announce Type: new Abstract: Wearable devices enable continuous, population-scale monitoring of physiological signals, such as photoplethysmography (PPG), creating new opportunities for data-driven clinical assessment. Time-series extrinsic regression (TSER) models increasingly leverage PPG signals t... | https://arxiv.org/abs/2601.10356 | Academic Papers | svg |
bb87c35ce95d3e434e4b456ef229bc916300d8d113d0e8e618adecf741439357 | 2026-01-16T00:00:00-05:00 | PLGC: Pseudo-Labeled Graph Condensation | arXiv:2601.10358v1 Announce Type: new Abstract: Large graph datasets make training graph neural networks (GNNs) computationally costly. Graph condensation methods address this by generating small synthetic graphs that approximate the original data. However, existing approaches rely on clean, supervised labels, which li... | https://arxiv.org/abs/2601.10358 | Academic Papers | svg |
6c3653e969483d9542a5b38cafbc991a9c905a292a4b77793b4d20e3421b62c3 | 2026-01-16T00:00:00-05:00 | Generalized Weight Structure of Polar Codes: Selected Template Polynomials | arXiv:2601.10362v1 Announce Type: new Abstract: Polar codes can be viewed as decreasing monomial codes, revealing a rich algebraic structure governed by the lower-triangular affine (LTA) group. We develop a general framework to compute the Hamming weight of codewords generated by sums of monomials, express these weight... | https://arxiv.org/abs/2601.10362 | Academic Papers | svg |
ac3f11b98352f53a64b4cee582f432bdc015d9d1c3ae759c7812587ac39d7544 | 2026-01-16T00:00:00-05:00 | FastStair: Learning to Run Up Stairs with Humanoid Robots | arXiv:2601.10365v1 Announce Type: new Abstract: Running up stairs is effortless for humans but remains extremely challenging for humanoid robots due to the simultaneous requirements of high agility and strict stability. Model-free reinforcement learning (RL) can generate dynamic locomotion, yet implicit stability rewar... | https://arxiv.org/abs/2601.10365 | Academic Papers | svg |
7d6263924498c1e66c7e598bdc2fdce918fad0a1af9626776335a9359b27c581 | 2026-01-16T00:00:00-05:00 | Inverse Learning in $2\times2$ Games: From Synthetic Interactions to Traffic Simulation | arXiv:2601.10367v1 Announce Type: new Abstract: Understanding how agents coordinate or compete from limited behavioral data is central to modeling strategic interactions in traffic, robotics, and other multi-agent systems. In this work, we investigate the following complementary formulations of inverse game-theoretic l... | https://arxiv.org/abs/2601.10367 | Academic Papers | svg |
29db87754cdc8c28afbc5e1c06374ab395d3c5e959f4cfdd0cc70fb51ef0b1de | 2026-01-16T00:00:00-05:00 | Fine-Grained Human Pose Editing Assessment via Layer-Selective MLLMs | arXiv:2601.10369v1 Announce Type: new Abstract: Text-guided human pose editing has gained significant traction in AIGC applications. However,it remains plagued by structural anomalies and generative artifacts. Existing evaluation metrics often isolate authenticity detection from quality assessment, failing to provide f... | https://arxiv.org/abs/2601.10369 | Academic Papers | svg |
d2be21cd8d22d5e50a5438eb21f9bedab6deafbe84e849c218093e15a14a2d93 | 2026-01-16T00:00:00-05:00 | Towards Efficient Low-rate Image Compression with Frequency-aware Diffusion Prior Refinement | arXiv:2601.10373v1 Announce Type: new Abstract: Recent advancements in diffusion-based generative priors have enabled visually plausible image compression at extremely low bit rates. However, existing approaches suffer from slow sampling processes and suboptimal bit allocation due to fragmented training paradigms. In t... | https://arxiv.org/abs/2601.10373 | Academic Papers | svg |
92021b588b124056ba1687a6912ecfe9f6d312c74ceba9ddd10adaef367b7b01 | 2026-01-16T00:00:00-05:00 | A Hybrid Reliability--Weight Framework for Construction of Polar Codes | arXiv:2601.10376v1 Announce Type: new Abstract: Polar codes are usually constructed by ranking synthetic bit-channels according to reliability, which guarantees capacity-achieving behavior but can yield poor low-weight spectra at short and moderate lengths. Recent algebraic results express the contribution of individua... | https://arxiv.org/abs/2601.10376 | Academic Papers | svg |
651de605f72de63f2b5363c43c0a9a32b91dbb788f128ee6d4b0145483d0396b | 2026-01-16T00:00:00-05:00 | Global Context Compression with Interleaved Vision-Text Transformation | arXiv:2601.10378v1 Announce Type: new Abstract: Recent achievements of vision-language models in end-to-end OCR point to a new avenue for low-loss compression of textual information. This motivates earlier works that render the Transformer's input into images for prefilling, which effectively reduces the number of toke... | https://arxiv.org/abs/2601.10378 | Academic Papers | svg |
86527c1fe15b466c9e7b57221d950b0b01abcc6a92bb6359ede69e447eb62125 | 2026-01-16T00:00:00-05:00 | Online identification of nonlinear time-varying systems with uncertain information | arXiv:2601.10379v1 Announce Type: new Abstract: Digital twins (DTs), serving as the core enablers for real-time monitoring and predictive maintenance of complex cyber-physical systems, impose critical requirements on their virtual models: high predictive accuracy, strong interpretability, and online adaptive capability... | https://arxiv.org/abs/2601.10379 | Academic Papers | svg |
e39416d651ceff3562dd0a54a142e7332dd5b01a08e0486ca40bfc9c023b5cbb | 2026-01-16T00:00:00-05:00 | Does Cognitive Load Affect Human Accuracy in Detecting Voice-Based Deepfakes? | arXiv:2601.10383v1 Announce Type: new Abstract: Deepfake technologies are powerful tools that can be misused for malicious purposes such as spreading disinformation on social media. The effectiveness of such malicious applications depends on the ability of deepfakes to deceive their audience. Therefore, researchers hav... | https://arxiv.org/abs/2601.10383 | Academic Papers | svg |
6f37df0783544b144e5219a8a54d513a2c7ec085fd2565b3644b777748230528 | 2026-01-16T00:00:00-05:00 | RSA-Bench: Benchmarking Audio Large Models in Real-World Acoustic Scenarios | arXiv:2601.10384v1 Announce Type: new Abstract: While Audio Large Models (ALMs) have achieved remarkable proficiency, their robustness remains brittle in real-world deployment. Existing evaluations largely rely on synthetic Gaussian noise or simplistic single-source interference, failing to capture the intricate, multi... | https://arxiv.org/abs/2601.10384 | Academic Papers | svg |
dcbdf401500f2ab9635b096312ea6d1da9b2d99cea087e1a3fbf79b03336a97f | 2026-01-16T00:00:00-05:00 | Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer | arXiv:2601.10386v1 Announce Type: new Abstract: Accurate survival prediction in Non-Small Cell Lung Cancer (NSCLC) requires the integration of heterogeneous clinical, radiological, and histopathological information. While Multimodal Deep Learning (MDL) offers a promises for precision prognosis and survival prediction, ... | https://arxiv.org/abs/2601.10386 | Academic Papers | svg |
ae9d5fb375d34917ae7ae0eade5a31f74ed9779b45cd3bd2d52b6442c5f56e1b | 2026-01-16T00:00:00-05:00 | The Assistant Axis: Situating and Stabilizing the Default Persona of Language Models | arXiv:2601.10387v1 Announce Type: new Abstract: Large language models can represent a variety of personas but typically default to a helpful Assistant identity cultivated during post-training. We investigate the structure of the space of model personas by extracting activation directions corresponding to diverse charac... | https://arxiv.org/abs/2601.10387 | Academic Papers | svg |
0fcdaf9d4de376e980877147f49f80cc21e901486d87c50d0d656120b3d256b7 | 2026-01-16T00:00:00-05:00 | INDIC DIALECT: A Multi Task Benchmark to Evaluate and Translate in Indian Language Dialects | arXiv:2601.10388v1 Announce Type: new Abstract: Recent NLP advances focus primarily on standardized languages, leaving most low-resource dialects under-served especially in Indian scenarios. In India, the issue is particularly important: despite Hindi being the third most spoken language globally (over 600 million spea... | https://arxiv.org/abs/2601.10388 | Academic Papers | svg |
87ba66090580d7caa0a191263724a0d8d2d814fc69674b497c52d2749702d350 | 2026-01-16T00:00:00-05:00 | Regularization of linear inverse problems by rational Krylov methods | arXiv:2601.10389v1 Announce Type: new Abstract: For approximately solving linear ill-posed problems in Hilbert spaces, we investigate the regularization properties of the aggregation method and the RatCG method. These recent algorithms use previously calculated solutions of Tikhonov regularization (respectively, Landwe... | https://arxiv.org/abs/2601.10389 | Academic Papers | svg |
a9f91125093f8c6a7865910bc5c3d767a5556b40b7abffd08a3735e85e26ae81 | 2026-01-16T00:00:00-05:00 | Codebook Design for Limited Feedback in Near-Field XL-MIMO Systems | arXiv:2601.10391v1 Announce Type: new Abstract: In this paper, we study efficient codebook design for limited feedback in extremely large-scale multiple-input-multiple-output (XL-MIMO) frequency division duplexing (FDD) systems. It is worth noting that existing codebook designs for XL-MIMO, such as polar-domain codeboo... | https://arxiv.org/abs/2601.10391 | Academic Papers | svg |
bb8793f123e39ffd757d5dde334e26cb395f988b9f9948653164d732aa0ae66d | 2026-01-16T00:00:00-05:00 | Multi-Temporal Frames Projection for Dynamic Processes Fusion in Fluorescence Microscopy | arXiv:2601.10392v1 Announce Type: new Abstract: Fluorescence microscopy is widely employed for the analysis of living biological samples; however, the utility of the resulting recordings is frequently constrained by noise, temporal variability, and inconsistent visualisation of signals that oscillate over time. We pres... | https://arxiv.org/abs/2601.10392 | Academic Papers | svg |
cf6bfa41f655862abae139e83704befb9f889b6515c5dc4db6c75e9790423dd5 | 2026-01-16T00:00:00-05:00 | Multiaccess Coded Caching with Heterogeneous Retrieval Costs | arXiv:2601.10394v1 Announce Type: new Abstract: The multiaccess coded caching (MACC) system, as formulated by Hachem {\it et al.}, consists of a central server with a library of $N$ files, connected to $K$ cache-less users via an error-free shared link, and $K$ cache nodes, each equipped with cache memory of size $M$ f... | https://arxiv.org/abs/2601.10394 | Academic Papers | svg |
093ea3382f8870048efbebd7db56cb53dfc25b216e59c65c5f3643778dbea607 | 2026-01-16T00:00:00-05:00 | LatentRefusal: Latent-Signal Refusal for Unanswerable Text-to-SQL Queries | arXiv:2601.10398v1 Announce Type: new Abstract: In LLM-based text-to-SQL systems, unanswerable and underspecified user queries may generate not only incorrect text but also executable programs that yield misleading results or violate safety constraints, posing a major barrier to safe deployment. Existing refusal strate... | https://arxiv.org/abs/2601.10398 | Academic Papers | svg |
7f2c0813d58381d10e1673c0f67126e013a3631d7f8c078ad7f86b1ef899ca09 | 2026-01-16T00:00:00-05:00 | A Geometric Multigrid Preconditioner for Shifted Boundary Method | arXiv:2601.10399v1 Announce Type: new Abstract: The Shifted Boundary Method (SBM) trades some part of the burden of body-fitted meshing for increased algebraic complexity. While the resulting linear systems retain the standard $\mathcal{O}(h^{-2})$ conditioning of second-order operators, the non-symmetry and non-local ... | https://arxiv.org/abs/2601.10399 | Academic Papers | svg |
46c7d933f9291cbd05bc731a0eea04af7b796da3c65d0e51b45adad21521d632 | 2026-01-16T00:00:00-05:00 | Toward Ultra-Long-Horizon Agentic Science: Cognitive Accumulation for Machine Learning Engineering | arXiv:2601.10402v1 Announce Type: new Abstract: The advancement of artificial intelligence toward agentic science is currently bottlenecked by the challenge of ultra-long-horizon autonomy, the ability to sustain strategic coherence and iterative correction over experimental cycles spanning days or weeks. While Large La... | https://arxiv.org/abs/2601.10402 | Academic Papers | svg |
3721d27ebb7073d5d99fa23cd13b48172261c20da59b7f5367c53e405ddf5bd2 | 2026-01-16T00:00:00-05:00 | Discrete Feynman-Kac Correctors | arXiv:2601.10403v1 Announce Type: new Abstract: Discrete diffusion models have recently emerged as a promising alternative to the autoregressive approach for generating discrete sequences. Sample generation via gradual denoising or demasking processes allows them to capture hierarchical non-sequential interdependencies... | https://arxiv.org/abs/2601.10403 | Academic Papers | svg |
5f5ec7654069a023a12f252f619a120486461ea3d7cdfbb97f4330c27ff1d2e2 | 2026-01-16T00:00:00-05:00 | ErrEval: Error-Aware Evaluation for Question Generation through Explicit Diagnostics | arXiv:2601.10406v1 Announce Type: new Abstract: Automatic Question Generation (QG) often produces outputs with critical defects, such as factual hallucinations and answer mismatches. However, existing evaluation methods, including LLM-based evaluators, mainly adopt a black-box and holistic paradigm without explicit err... | https://arxiv.org/abs/2601.10406 | Academic Papers | svg |
723b471667624772bb71ad2eb6fe1748fb3c57864282a057d0a763250c458644 | 2026-01-16T00:00:00-05:00 | CS-GBA: A Critical Sample-based Gradient-guided Backdoor Attack for Offline Reinforcement Learning | arXiv:2601.10407v1 Announce Type: new Abstract: Offline Reinforcement Learning (RL) enables policy optimization from static datasets but is inherently vulnerable to backdoor attacks. Existing attack strategies typically struggle against safety-constrained algorithms (e.g., CQL) due to inefficient random poisoning and t... | https://arxiv.org/abs/2601.10407 | Academic Papers | svg |
07c10df31c53956d229d7e575ca097a04d033bf5713194492d2f1ae6db310878 | 2026-01-16T00:00:00-05:00 | TF3-RO-50M: Training Compact Romanian Language Models from Scratch on Synthetic Moral Microfiction | arXiv:2601.10410v1 Announce Type: new Abstract: Recent advances in synthetic data generation have shown that compact language models can be trained effectively when the underlying corpus is structurally controlled and linguistically coherent. However, for morphologically rich and computationally under-resourced languag... | https://arxiv.org/abs/2601.10410 | Academic Papers | svg |
f2a2db8980446a5444cd79be87fca8ed8b4c66e6f2b8db83322d72a9c068d899 | 2026-01-16T00:00:00-05:00 | LADFA: A Framework of Using Large Language Models and Retrieval-Augmented Generation for Personal Data Flow Analysis in Privacy Policies | arXiv:2601.10413v1 Announce Type: new Abstract: Privacy policies help inform people about organisations' personal data processing practices, covering different aspects such as data collection, data storage, and sharing of personal data with third parties. Privacy policies are often difficult for people to fully compreh... | https://arxiv.org/abs/2601.10413 | Academic Papers | svg |
4291d3bb480546fff9e2579440b6f67e4b6d45778a35f855a9d1270bc3ef30bd | 2026-01-16T00:00:00-05:00 | LLMdoctor: Token-Level Flow-Guided Preference Optimization for Efficient Test-Time Alignment of Large Language Models | arXiv:2601.10416v1 Announce Type: new Abstract: Aligning Large Language Models (LLMs) with human preferences is critical, yet traditional fine-tuning methods are computationally expensive and inflexible. While test-time alignment offers a promising alternative, existing approaches often rely on distorted trajectory-lev... | https://arxiv.org/abs/2601.10416 | Academic Papers | svg |
152fdfc483de52a9e481aef8f98ee9b407ef92a42e9e0b24f9bb75e159efda6e | 2026-01-16T00:00:00-05:00 | Reinforcement Learning with Multi-Step Lookahead Information Via Adaptive Batching | arXiv:2601.10418v1 Announce Type: new Abstract: We study tabular reinforcement learning problems with multiple steps of lookahead information. Before acting, the learner observes $\ell$ steps of future transition and reward realizations: the exact state the agent would reach and the rewards it would collect under any p... | https://arxiv.org/abs/2601.10418 | Academic Papers | svg |
41a7793e11e2d350cb0be30abf0f97a918f69ad299b8271d68285841da99fde5 | 2026-01-16T00:00:00-05:00 | Are Language Models Models? | arXiv:2601.10421v1 Announce Type: new Abstract: Futrell and Mahowald claim LMs "serve as model systems", but an assessment at each of Marr's three levels suggests the claim is clearly not true at the implementation level, poorly motivated at the algorithmic-representational level, and problematic at the computational t... | https://arxiv.org/abs/2601.10421 | Academic Papers | svg |
9005a5c600a4f9cf115d44b19957728bfb11e5bb492ab1375230c324e2e67b2e | 2026-01-16T00:00:00-05:00 | Placement Delivery Array for Cache-Aided MIMO Systems | arXiv:2601.10422v1 Announce Type: new Abstract: We consider a $(G,L,K,M,N)$ cache-aided multiple-input multiple-output (MIMO) network, where a server equipped with $L$ antennas and a library of $N$ equal-size files communicates with $K$ users, each equipped with $G$ antennas and a cache of size $M$ files, over a wirele... | https://arxiv.org/abs/2601.10422 | Academic Papers | svg |
566113a2b5965095fc659d4eba5e585e13676517dac6d360dbe194629bbed915 | 2026-01-16T00:00:00-05:00 | Aletheia-Probe: A Tool for Automated Journal Assessment | arXiv:2601.10431v1 Announce Type: new Abstract: Assessing journal legitimacy during literature reviews, publication venue selection, and citation verification requires consulting information scattered across multiple incompatible data-sets. This paper introduces Aletheia-Probe, an open-source tool that systematically a... | https://arxiv.org/abs/2601.10431 | Academic Papers | svg |
48edbd1ed3b4000d1faeb29bf83226eeddbeded9fbbc42de7e613d2639c79cf8 | 2026-01-16T00:00:00-05:00 | Development of Ontological Knowledge Bases by Leveraging Large Language Models | arXiv:2601.10436v1 Announce Type: new Abstract: Ontological Knowledge Bases (OKBs) play a vital role in structuring domain-specific knowledge and serve as a foundation for effective knowledge management systems. However, their traditional manual development poses significant challenges related to scalability, consisten... | https://arxiv.org/abs/2601.10436 | Academic Papers | svg |
77208429a66b8ab5c0142fc52497b3383b588d9bdf5106ccfe34e91001629862 | 2026-01-16T00:00:00-05:00 | AgentGuardian: Learning Access Control Policies to Govern AI Agent Behavior | arXiv:2601.10440v1 Announce Type: new Abstract: Artificial intelligence (AI) agents are increasingly used in a variety of domains to automate tasks, interact with users, and make decisions based on data inputs. Ensuring that AI agents perform only authorized actions and handle inputs appropriately is essential for main... | https://arxiv.org/abs/2601.10440 | Academic Papers | svg |
65746ebdc47348287a6d1755f80dacc3731e45db52c0e1359aa34f3890216e28 | 2026-01-16T00:00:00-05:00 | Subjective evaluation of UHD video coded using VVC with LCEVC and ML-VVC | arXiv:2601.10448v1 Announce Type: new Abstract: This paper presents the results of a subjective quality assessment of a multilayer video coding configuration in which Low Complexity Enhancement Video Coding (LCEVC) is applied as an enhancement layer on top of a Versatile Video Coding (VVC) base layer. The evaluation fo... | https://arxiv.org/abs/2601.10448 | Academic Papers | svg |
817eaa315745c37acb9e883e1b43f4174cdcd54d8c8c28c07e6d4612b2a3ac4f | 2026-01-16T00:00:00-05:00 | Lunar-G2R: Geometry-to-Reflectance Learning for High-Fidelity Lunar BRDF Estimation | arXiv:2601.10449v1 Announce Type: new Abstract: We address the problem of estimating realistic, spatially varying reflectance for complex planetary surfaces such as the lunar regolith, which is critical for high-fidelity rendering and vision-based navigation. Existing lunar rendering pipelines rely on simplified or spa... | https://arxiv.org/abs/2601.10449 | Academic Papers | svg |
4daefb2b7d9b2585be3db0caa6abcccafaae728d2db96fc1a2d483e52034d7b8 | 2026-01-16T00:00:00-05:00 | Energy-Efficient Probabilistic Semantic Communication Over Visible Light Networks With Rate Splitting | arXiv:2601.10452v1 Announce Type: new Abstract: Visible light communication (VLC) is emerging as a key technology for future wireless communication systems due to its unique physical-layer advantages over traditional radio-frequency (RF)-based systems. However, its integration with higher-layer techniques, such as sema... | https://arxiv.org/abs/2601.10452 | Academic Papers | svg |
555439042609c26558470e27502bad75b3039505fc57ac7b1a41063d372d46fb | 2026-01-16T00:00:00-05:00 | Stable Differentiable Modal Synthesis for Learning Nonlinear Dynamics | arXiv:2601.10453v1 Announce Type: new Abstract: Modal methods are a long-standing approach to physical modelling synthesis. Extensions to nonlinear problems are possible, including the case of a high-amplitude vibration of a string. A modal decomposition leads to a densely coupled nonlinear system of ordinary different... | https://arxiv.org/abs/2601.10453 | Academic Papers | svg |
b24a0a877f513411207fd3fc021f55484750c03e7ed1c41d6e1a36ca7ae17f06 | 2026-01-16T00:00:00-05:00 | SurgGoal: Rethinking Surgical Planning Evaluation via Goal-Satisfiability | arXiv:2601.10455v1 Announce Type: new Abstract: Surgical planning integrates visual perception, long-horizon reasoning, and procedural knowledge, yet it remains unclear whether current evaluation protocols reliably assess vision-language models (VLMs) in safety-critical settings. Motivated by a goal-oriented view of su... | https://arxiv.org/abs/2601.10455 | Academic Papers | svg |
b54afb1afe42ef57cfce1e48fb2e39ee421d63c98a3bbd5d2a072746c2cfd9ad | 2026-01-16T00:00:00-05:00 | NSR-Boost: A Neuro-Symbolic Residual Boosting Framework for Industrial Legacy Models | arXiv:2601.10457v1 Announce Type: new Abstract: Although the Gradient Boosted Decision Trees (GBDTs) dominate industrial tabular applications, upgrading legacy models in high-concurrency production environments still faces prohibitive retraining costs and systemic risks. To address this problem, we present NSR-Boost, a... | https://arxiv.org/abs/2601.10457 | Academic Papers | svg |
39c8f04c55e639e96d5e5676b758d64c99772d97a112db6eb57e4f23983f96a4 | 2026-01-16T00:00:00-05:00 | LangLasso: Interactive Cluster Descriptions through LLM Explanation | arXiv:2601.10458v1 Announce Type: new Abstract: Dimensionality reduction is a powerful technique for revealing structure and potential clusters in data. However, as the axes are complex, non-linear combinations of features, they often lack semantic interpretability. Existing visual analytics (VA) methods support cluste... | https://arxiv.org/abs/2601.10458 | Academic Papers | svg |
6809f5f8a325acbb0f3c2b93480288b04544dae28d8d2504ea544f739f8e04b7 | 2026-01-16T00:00:00-05:00 | Contextual StereoSet: Stress-Testing Bias Alignment Robustness in Large Language Models | arXiv:2601.10460v1 Announce Type: new Abstract: A model that avoids stereotypes in a lab benchmark may not avoid them in deployment. We show that measured bias shifts dramatically when prompts mention different places, times, or audiences -- no adversarial prompting required. We introduce Contextual StereoSet, a benchm... | https://arxiv.org/abs/2601.10460 | Academic Papers | svg |
d0e53fc6e14405349886fa9d63c1310534b53c2eb4f3d19ff01a667de9efe2de | 2026-01-16T00:00:00-05:00 | ChartComplete: A Taxonomy-based Inclusive Chart Dataset | arXiv:2601.10462v1 Announce Type: new Abstract: With advancements in deep learning (DL) and computer vision techniques, the field of chart understanding is evolving rapidly. In particular, multimodal large language models (MLLMs) are proving to be efficient and accurate in understanding charts. To accurately measure th... | https://arxiv.org/abs/2601.10462 | Academic Papers | svg |
c5951e960188de4006cb1a3aea844cc40a01dfaffda0bfd214f8fcecff6e9800 | 2026-01-16T00:00:00-05:00 | Architectural Classification of XR Workloads: Cross-Layer Archetypes and Implications | arXiv:2601.10463v1 Announce Type: new Abstract: Edge and mobile platforms for augmented and virtual reality, collectively referred to as extended reality (XR) must deliver deterministic ultra-low-latency performance under stringent power and area constraints. However, the diversity of XR workloads is rapidly increasing... | https://arxiv.org/abs/2601.10463 | Academic Papers | svg |
bcafba33e3e8c4e817eab5c499b8b15d3bd764954dbccdac3398e69b471a6c72 | 2026-01-16T00:00:00-05:00 | AI Sycophancy: How Users Flag and Respond | arXiv:2601.10467v1 Announce Type: new Abstract: While concerns about LLM sycophancy have grown among researchers and developers, how users themselves experience this behavior remains largely unexplored. We analyze Reddit discussions to investigate how users detect, mitigate, and perceive sycophantic AI. We develop the ... | https://arxiv.org/abs/2601.10467 | Academic Papers | svg |
7b9e8c95babee3e0f5ef99124bbca87cabcf5df3ab9ad25a7256b5fea4262c2f | 2026-01-16T00:00:00-05:00 | Job Anxiety in Post-Secondary Computer Science Students Caused by Artificial Intelligence | arXiv:2601.10468v1 Announce Type: new Abstract: The emerging widespread usage of AI has led to industry adoption to improve efficiency and increase earnings. However, a major consequence of this is AI displacing employees from their jobs, leading to feelings of job insecurity and uncertainty. This is especially true fo... | https://arxiv.org/abs/2601.10468 | Academic Papers | svg |
fded440f3295d5eb14ab2072fab15891e91a809579c8ed55787df5c9c5ac3980 | 2026-01-16T00:00:00-05:00 | Joint Source-Channel Coding for ISAC: Distortion Tradeoffs and Separation Theorems | arXiv:2601.10470v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) systems have garnered significant attention due to their capability to simultaneously achieve efficient communication and environmental sensing. A core objective in this field is characterizing the performance tradeoff between s... | https://arxiv.org/abs/2601.10470 | Academic Papers | svg |
ccdf2308581084ca7cdf9444e5e23b5a5bcedfe151fc3503f67b1586f18ec11e | 2026-01-16T00:00:00-05:00 | DeFlow: Decoupling Manifold Modeling and Value Maximization for Offline Policy Extraction | arXiv:2601.10471v1 Announce Type: new Abstract: We present DeFlow, a decoupled offline RL framework that leverages flow matching to faithfully capture complex behavior manifolds. Optimizing generative policies is computationally prohibitive, typically necessitating backpropagation through ODE solvers. We address this b... | https://arxiv.org/abs/2601.10471 | Academic Papers | svg |
a0afb9d9e589378839c54b8a2349c54541936586452e14c2c3416b8f9dadd132 | 2026-01-16T00:00:00-05:00 | Optimal error estimates for a discontinuous Galerkin method on curved boundaries with polygonal meshes | arXiv:2601.10474v1 Announce Type: new Abstract: We consider a discontinuous Galerkin method for the numerical solution of boundary value problems in two-dimensional domains with curved boundaries. A key challenge in this setting is the potential loss of convergence order due to approximating the physical domain by a po... | https://arxiv.org/abs/2601.10474 | Academic Papers | svg |
88ad1d2cdd5d3914527e6e090030bbad53e9ce95d61ddda68521b254cb5640d7 | 2026-01-16T00:00:00-05:00 | Urban Socio-Semantic Segmentation with Vision-Language Reasoning | arXiv:2601.10477v1 Announce Type: new Abstract: As hubs of human activity, urban surfaces consist of a wealth of semantic entities. Segmenting these various entities from satellite imagery is crucial for a range of downstream applications. Current advanced segmentation models can reliably segment entities defined by ph... | https://arxiv.org/abs/2601.10477 | Academic Papers | svg |
bbf03eb33065b6af2ac734e00c2225db63deac9cdccdcab4d1a4648bc0b9ea59 | 2026-01-16T00:00:00-05:00 | A Construction Framework of Coded Caching Scheme for Multi-Access MIMO Systems via Knapsack Problem | arXiv:2601.10484v1 Announce Type: new Abstract: This paper investigates the coded caching problem in a multi-access multiple-input single-output (MAMISO) network with the combinatorial topology. The considered system consists of a server containing $N$ files, $\Lambda$ cache nodes, and $K$ cache-less users, where each ... | https://arxiv.org/abs/2601.10484 | Academic Papers | svg |
36d93daf20f9556679d903f7b3ffb5b5af5efb9eba2ce61102303d90ddde2629 | 2026-01-16T00:00:00-05:00 | Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge | arXiv:2601.10485v1 Announce Type: new Abstract: Domain-specific knowledge graphs (DKGs) often lack coverage compared to general knowledge graphs (GKGs). To address this, we introduce Domain-specific Knowledge Graph Fusion (DKGF), a novel task that enriches DKGs by integrating relevant facts from GKGs. DKGF faces two ke... | https://arxiv.org/abs/2601.10485 | Academic Papers | svg |
006f1796f59c83c70d141504d4a4a7a302fd5c0cf4145007770f028b0089d25a | 2026-01-16T00:00:00-05:00 | Communication-Efficient Federated Learning by Exploiting Spatio-Temporal Correlations of Gradients | arXiv:2601.10491v1 Announce Type: new Abstract: Communication overhead is a critical challenge in federated learning, particularly in bandwidth-constrained networks. Although many methods have been proposed to reduce communication overhead, most focus solely on compressing individual gradients, overlooking the temporal... | https://arxiv.org/abs/2601.10491 | Academic Papers | svg |
5a87650646d914e4429f7c85f5fd6546b9cbeba1a01cc45b46a0b9d260afda81 | 2026-01-16T00:00:00-05:00 | Model See, Model Do? Exposure-Aware Evaluation of Bug-vs-Fix Preference in Code LLMs | arXiv:2601.10496v1 Announce Type: new Abstract: Large language models are increasingly used for code generation and debugging, but their outputs can still contain bugs, that originate from training data. Distinguishing whether an LLM prefers correct code, or a familiar incorrect version might be influenced by what it's... | https://arxiv.org/abs/2601.10496 | Academic Papers | svg |
094f6d42371bed7938bc04a976133ad78e69377c37f9caedd37559268238445b | 2026-01-16T00:00:00-05:00 | mergetune: Continued fine-tuning of vision-language models | arXiv:2601.10497v1 Announce Type: new Abstract: Fine-tuning vision-language models (VLMs) such as CLIP often leads to catastrophic forgetting of pretrained knowledge. Prior work primarily aims to mitigate forgetting during adaptation; however, forgetting often remains inevitable during this process. We introduce a nove... | https://arxiv.org/abs/2601.10497 | Academic Papers | svg |
c7e6263aa4d061580dfea4ddf4885a4c77851b437d5a19d22f044d60600e6abf | 2026-01-16T00:00:00-05:00 | Projected Microbatch Accumulation yields reference-free proximal policy updates for reinforcement learning | arXiv:2601.10498v1 Announce Type: new Abstract: This note introduces Projected Microbatch Accumulation (PROMA), a proximal policy update method for large language model fine-tuning. PROMA accumulates policy gradients across microbatches by projecting out sequence-wise gradient components before microbatch aggregation. ... | https://arxiv.org/abs/2601.10498 | Academic Papers | svg |
c083d3d650fa51d6278fe4eac25da9dca95d624187d6d69c9eb659079d0fe678 | 2026-01-16T00:00:00-05:00 | Higher order trade-offs in hypergraph community detection | arXiv:2601.10502v1 Announce Type: new Abstract: Extending community detection from pairwise networks to hypergraphs introduces fundamental theoretical challenges. Hypergraphs exhibit structural heterogeneity with no direct graph analogue: hyperedges of varying orders can connect nodes across communities in diverse conf... | https://arxiv.org/abs/2601.10502 | Academic Papers | svg |
ad479dd705b36bf3fc0f748cc7cf48e55bd1f5f5b03dd62343c6f1aee739f3da | 2026-01-16T00:00:00-05:00 | Coded Caching for Combinatorial Multi-Access Hotplug Networks from $t$-Designs | arXiv:2601.10503v1 Announce Type: new Abstract: We study hotplug coded caching in combinatorial multi-access networks, which generalizes existing hotplug coded caching models by allowing users to access multiple caches, while only a subset of caches is online during the delivery phase. We first generalize the Hotplug P... | https://arxiv.org/abs/2601.10503 | Academic Papers | svg |
bc2406e1f621ce06c20fa6aa83da7542d1d78808c285397ca0c064a89b3be34d | 2026-01-16T00:00:00-05:00 | DR-Arena: an Automated Evaluation Framework for Deep Research Agents | arXiv:2601.10504v1 Announce Type: new Abstract: As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, reliable evaluation of their task performance has become a critical bottleneck. Current benchmarks predominantly rely on static... | https://arxiv.org/abs/2601.10504 | Academic Papers | svg |
2dd55060616917b4d4ef2560f579e3892216197956b9bf8f797a89c80afdfef3 | 2026-01-16T00:00:00-05:00 | A New Construction Structure on Coded Caching with Linear Subpacketization: Non-Half-Sum Latin Rectangle | arXiv:2601.10505v1 Announce Type: new Abstract: Coded caching is recognized as an effective method for alleviating network congestion during peak periods by leveraging local caching and coded multicasting gains. The key challenge in designing coded caching schemes lies in simultaneously achieving low subpacketization a... | https://arxiv.org/abs/2601.10505 | Academic Papers | svg |
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