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9bb7ba45bd5f28f1f1ebbadd8b1d2679d2af2b0e22d39a7e258d109895a90c6b | 2026-01-23T00:00:00-05:00 | ViT Registers and Fractal ViT | arXiv:2601.15506v1 Announce Type: new Abstract: Drawing inspiration from recent findings including surprisingly decent performance of transformers without positional encoding (NoPE) in the domain of language models and how registers (additional throwaway tokens not tied to input) may improve the performance of large vi... | https://arxiv.org/abs/2601.15506 | Academic Papers | svg |
47247582ee947d8ba882682774bac305398a0de5dff31ac90de2c1c150dd4bee | 2026-01-23T00:00:00-05:00 | Controllable Layered Image Generation for Real-World Editing | arXiv:2601.15507v1 Announce Type: new Abstract: Recent image generation models have shown impressive progress, yet they often struggle to yield controllable and consistent results when users attempt to edit specific elements within an existing image. Layered representations enable flexible, user-driven content creation... | https://arxiv.org/abs/2601.15507 | Academic Papers | svg |
1264eadf77054b7d7f04a8dd5562303334dba744f11b3e91a22d38ce78ac316d | 2026-01-23T00:00:00-05:00 | Computational Representations of Character Significance in Novels | arXiv:2601.15508v1 Announce Type: new Abstract: Characters in novels have typically been modeled based on their presence in scenes in narrative, considering aspects like their actions, named mentions, and dialogue. This conception of character places significant emphasis on the main character who is present in the most... | https://arxiv.org/abs/2601.15508 | Academic Papers | svg |
f97d302c1addd24cc51d156eeda41aa0b5df805d6dab83fc748208a0bf4f3502 | 2026-01-23T00:00:00-05:00 | The Dark Side of AI Transformers: Sentiment Polarization & the Loss of Business Neutrality by NLP Transformers | arXiv:2601.15509v1 Announce Type: new Abstract: The use of Transfer Learning & Transformers has steadily improved accuracy and has significantly contributed in solving complex computation problems. However, this transformer led accuracy improvement in Applied AI Analytics specifically in sentiment analytics comes with ... | https://arxiv.org/abs/2601.15509 | Academic Papers | svg |
ec7497c8bd41c91618b63b676ce6449784a0119261dabde56c9f72c36cd61e14 | 2026-01-23T00:00:00-05:00 | AdversaRiskQA: An Adversarial Factuality Benchmark for High-Risk Domains | arXiv:2601.15511v1 Announce Type: new Abstract: Hallucination in large language models (LLMs) remains an acute concern, contributing to the spread of misinformation and diminished public trust, particularly in high-risk domains. Among hallucination types, factuality is crucial, as it concerns a model's alignment with e... | https://arxiv.org/abs/2601.15511 | Academic Papers | svg |
6a92b19cf554ad09f4c91936cac3d7cead808fb1e7f6d818f727e6c047746705 | 2026-01-23T00:00:00-05:00 | DCeption: Real-world Wireless Man-in-the-Middle Attacks Against CCS EV Charging | arXiv:2601.15515v1 Announce Type: new Abstract: The adoption of Electric Vehicles (EVs) is happening at a rapid pace. To ensure fast and safe charging, complex communication is required between the vehicle and the charging station. In the globally used Combined Charging System (CCS), this communication is carried over ... | https://arxiv.org/abs/2601.15515 | Academic Papers | svg |
c404b9bf0c20b07062d06f9a32fd33069efaf3ab382b068b1905976fd8c787d7 | 2026-01-23T00:00:00-05:00 | DeltaDorsal: Enhancing Hand Pose Estimation with Dorsal Features in Egocentric Views | arXiv:2601.15516v1 Announce Type: new Abstract: The proliferation of XR devices has made egocentric hand pose estimation a vital task, yet this perspective is inherently challenged by frequent finger occlusions. To address this, we propose a novel approach that leverages the rich information in dorsal hand skin deforma... | https://arxiv.org/abs/2601.15516 | Academic Papers | svg |
63a611662bd0c32f44ff02b226c8c04c89272e48086557d314807265058e68dd | 2026-01-23T00:00:00-05:00 | DS@GT at TREC TOT 2025: Bridging Vague Recollection with Fusion Retrieval and Learned Reranking | arXiv:2601.15518v1 Announce Type: new Abstract: We develop a two-stage retrieval system that combines multiple complementary retrieval methods with a learned reranker and LLM-based reranking, to address the TREC Tip-of-the-Tongue (ToT) task. In the first stage, we employ hybrid retrieval that merges LLM-based retrieval... | https://arxiv.org/abs/2601.15518 | Academic Papers | svg |
a763ceb21a3bd1b57ff021e52318060a93d659a71149d1a23e0af29945c77384 | 2026-01-23T00:00:00-05:00 | TransportAgents: a multi-agents LLM framework for traffic accident severity prediction | arXiv:2601.15519v1 Announce Type: new Abstract: Accurate prediction of traffic crash severity is critical for improving emergency response and public safety planning. Although recent large language models (LLMs) exhibit strong reasoning capabilities, their single-agent architectures often struggle with heterogeneous, d... | https://arxiv.org/abs/2601.15519 | Academic Papers | svg |
8ebb5e1c8e4196d010113bfcbc1120d53208c4df50003fa1c69b0548c2a9fc8a | 2026-01-23T00:00:00-05:00 | Securing LLM-as-a-Service for Small Businesses: An Industry Case Study of a Distributed Chatbot Deployment Platform | arXiv:2601.15528v1 Announce Type: new Abstract: Large Language Model (LLM)-based question-answering systems offer significant potential for automating customer support and internal knowledge access in small businesses, yet their practical deployment remains challenging due to infrastructure costs, engineering complexit... | https://arxiv.org/abs/2601.15528 | Academic Papers | svg |
caa16e56aec826aa6478364445c8612788baa2f982001d8dd7ee38d4ae7a9717 | 2026-01-23T00:00:00-05:00 | Machine learning-enhanced non-amnestic Alzheimer's disease diagnosis from MRI and clinical features | arXiv:2601.15530v1 Announce Type: new Abstract: Alzheimer's disease (AD), defined as an abnormal buildup of amyloid plaques and tau tangles in the brain can be diagnosed with high accuracy based on protein biomarkers via PET or CSF analysis. However, due to the invasive nature of biomarker collection, most AD diagnoses... | https://arxiv.org/abs/2601.15530 | Academic Papers | svg |
63e3d680e29f02de9144032d7bf63e2046f260ab35f716dbb735466dac799128 | 2026-01-23T00:00:00-05:00 | Resource Allocation and Sharing for UAV-Assisted Integrated TN-NTN with Multi-Connectivity | arXiv:2601.15532v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) with multi- connectivity (MC) capabilities efficiently and reliably transfer data between terrestrial networks (TNs) and non-terrestrial networks (NTNs). However, optimally sharing and allocating spectrum and power resources to maintain MC ... | https://arxiv.org/abs/2601.15532 | Academic Papers | svg |
29d8c1fdb4b4ae989bd277c43be13add6a94d3a1a06a7217ef1afc9723dff2bf | 2026-01-23T00:00:00-05:00 | From Generative Engines to Actionable Simulators: The Imperative of Physical Grounding in World Models | arXiv:2601.15533v1 Announce Type: new Abstract: A world model is an AI system that simulates how an environment evolves under actions, enabling planning through imagined futures rather than reactive perception. Current world models, however, suffer from visual conflation: the mistaken assumption that high-fidelity vide... | https://arxiv.org/abs/2601.15533 | Academic Papers | svg |
1f4bd46bf6f0436e9ffae97f4ec25ba053789d7368339ce893258fa7564274cf | 2026-01-23T00:00:00-05:00 | QUAIL: Quantization Aware Unlearning for Mitigating Misinformation in LLMs | arXiv:2601.15538v1 Announce Type: new Abstract: Machine unlearning aims to remove specific knowledge (e.g., copyrighted or private data) from a trained model without full retraining. In practice, models are often quantized (e.g., 4-bit) for deployment, but we find that quantization can catastrophically restore forgotte... | https://arxiv.org/abs/2601.15538 | Academic Papers | svg |
df321ceb6ff05fc2e20b9c9c5032c96ab492048df679e00ef0583df82a161528 | 2026-01-23T00:00:00-05:00 | PRISM: Deriving the Transformer as a Signal-Denoising Operator via Maximum Coding Rate Reduction | arXiv:2601.15540v1 Announce Type: new Abstract: Deep learning models, particularly Transformers, are often criticized as "black boxes" and lack interpretability. We propose Prism, a white-box attention-based architecture derived from the principles of Maximizing Coding Rate Reduction ($\text{MCR}^2$). By modeling the a... | https://arxiv.org/abs/2601.15540 | Academic Papers | svg |
47700241fed5fcccf2559cad417167e42abf0d3934c50c7654156c0f58c0ff36 | 2026-01-23T00:00:00-05:00 | CompliantVLA-adaptor: VLM-Guided Variable Impedance Action for Safe Contact-Rich Manipulation | arXiv:2601.15541v1 Announce Type: new Abstract: We propose a CompliantVLA-adaptor that augments the state-of-the-art Vision-Language-Action (VLA) models with vision-language model (VLM)-informed context-aware variable impedance control (VIC) to improve the safety and effectiveness of contact-rich robotic manipulation t... | https://arxiv.org/abs/2601.15541 | Academic Papers | svg |
cd8bef70563293811ee7efb0132abd134b48c01614c602b4a778fd096a796012 | 2026-01-23T00:00:00-05:00 | RDumb++: Drift-Aware Continual Test-Time Adaptation | arXiv:2601.15544v1 Announce Type: new Abstract: Continual Test-Time Adaptation (CTTA) seeks to update a pretrained model during deployment using only the incoming, unlabeled data stream. Although prior approaches such as Tent, EATA etc. provide meaningful improvements under short evolving shifts, they struggle when the... | https://arxiv.org/abs/2601.15544 | Academic Papers | svg |
076bd843ff19b6c194fe85752e1ad63c5a7ad61092f59913b426397ad1e60dcd | 2026-01-23T00:00:00-05:00 | A Mobile Magnetic Manipulation Platform for Gastrointestinal Navigation with Deep Reinforcement Learning Control | arXiv:2601.15545v1 Announce Type: new Abstract: Targeted drug delivery in the gastrointestinal (GI) tract using magnetic robots offers a promising alternative to systemic treatments. However, controlling these robots is a major challenge. Stationary magnetic systems have a limited workspace, while mobile systems (e.g.,... | https://arxiv.org/abs/2601.15545 | Academic Papers | svg |
9e83a5595681c9f18a15611d92645b2b8afdfeb686e34a4a1a2c69c1adfa4d4e | 2026-01-23T00:00:00-05:00 | Beyond validation loss: Clinically-tailored optimization metrics improve a model's clinical performance | arXiv:2601.15546v1 Announce Type: new Abstract: A key task in ML is to optimize models at various stages, e.g. by choosing hyperparameters or picking a stopping point. A traditional ML approach is to use validation loss, i.e. to apply the training loss function on a validation set to guide these optimizations. However,... | https://arxiv.org/abs/2601.15546 | Academic Papers | svg |
fbc32842ffe0b5a2b07df63bf0b0732070d4115a80c69952808cd6f56269cffc | 2026-01-23T00:00:00-05:00 | Learning Neural Operators from Partial Observations via Latent Autoregressive Modeling | arXiv:2601.15547v1 Announce Type: new Abstract: Real-world scientific applications frequently encounter incomplete observational data due to sensor limitations, geographic constraints, or measurement costs. Although neural operators significantly advanced PDE solving in terms of computational efficiency and accuracy, t... | https://arxiv.org/abs/2601.15547 | Academic Papers | svg |
d76e525b63fed8dedeb9ce3c1e4d1eb517b13648bea5c9f1b36bb27e81569c22 | 2026-01-23T00:00:00-05:00 | VIOLA: Towards Video In-Context Learning with Minimal Annotations | arXiv:2601.15549v1 Announce Type: new Abstract: Generalizing Multimodal Large Language Models (MLLMs) to novel video domains is essential for real-world deployment but remains challenging due to the scarcity of labeled data. While In-Context Learning (ICL) offers a training-free adaptation path, standard methods rely o... | https://arxiv.org/abs/2601.15549 | Academic Papers | svg |
1202610f23c9ef079ad5fae8b211d3224d4c41b108c28460ab67da4f3f72e42e | 2026-01-23T00:00:00-05:00 | Common to Whom? Regional Cultural Commonsense and LLM Bias in India | arXiv:2601.15550v1 Announce Type: new Abstract: Existing cultural commonsense benchmarks treat nations as monolithic, assuming uniform practices within national boundaries. But does cultural commonsense hold uniformly within a nation, or does it vary at the sub-national level? We introduce Indica, the first benchmark d... | https://arxiv.org/abs/2601.15550 | Academic Papers | svg |
1b972b1800dc29cd57fe87f154e07541e8c3198243c8f247aaeb4ffa57583442 | 2026-01-23T00:00:00-05:00 | ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance | arXiv:2601.15551v1 Announce Type: new Abstract: Personalized learning systems have emerged as a promising approach to enhance student outcomes by tailoring educational content, pacing, and feedback to individual needs. However, most existing systems remain fragmented, specializing in either knowledge tracing, diagnosti... | https://arxiv.org/abs/2601.15551 | Academic Papers | svg |
539bb187bb0b5f554c94c13f038e592f26de87e99d66b53b66d14b6cb31f41c1 | 2026-01-23T00:00:00-05:00 | BanditLP: Large-Scale Stochastic Optimization for Personalized Recommendations | arXiv:2601.15552v1 Announce Type: new Abstract: We present BanditLP, a scalable multi-stakeholder contextual bandit framework that unifies neural Thompson Sampling for learning objective-specific outcomes with a large-scale linear program for constrained action selection at serving time. The methodology is application-... | https://arxiv.org/abs/2601.15552 | Academic Papers | svg |
b7591aa269ddd4c3a612791e7d82acefc25e9f4c98db742b4a7e97ef80a332c0 | 2026-01-23T00:00:00-05:00 | LLM or Human? Perceptions of Trust and Information Quality in Research Summaries | arXiv:2601.15556v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate and edit scientific abstracts, yet their integration into academic writing raises questions about trust, quality, and disclosure. Despite growing adoption, little is known about how readers perceive LLM-genera... | https://arxiv.org/abs/2601.15556 | Academic Papers | svg |
904c4b179f36ce72b1a137fd81cc3461ce7a96b7759747d942ca12865f2ac393 | 2026-01-23T00:00:00-05:00 | From Generation to Collaboration: Using LLMs to Edit for Empathy in Healthcare | arXiv:2601.15558v1 Announce Type: new Abstract: Clinical empathy is essential for patient care, but physicians need continually balance emotional warmth with factual precision under the cognitive and emotional constraints of clinical practice. This study investigates how large language models (LLMs) can function as emp... | https://arxiv.org/abs/2601.15558 | Academic Papers | svg |
9244aa8dba91d140ddaa303e2bd282b0b444926f378d163d91d8f40e9bbc1d79 | 2026-01-23T00:00:00-05:00 | Relative Classification Accuracy: A Calibrated Metric for Identity Consistency in Fine-Grained K-pop Face Generation | arXiv:2601.15560v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models (DDPMs) have achieved remarkable success in high-fidelity image generation. However, evaluating their semantic controllability-specifically for fine-grained, single-domain tasks-remains challenging. Standard metrics like FID and In... | https://arxiv.org/abs/2601.15560 | Academic Papers | svg |
eb5420151442916598664417638e4afae994e285c41a7c64323c3797ec64a0e4 | 2026-01-23T00:00:00-05:00 | Enhanced Convergence in p-bit Based Simulated Annealing with Partial Deactivation for Large-Scale Combinatorial Optimization Problems | arXiv:2601.15561v1 Announce Type: new Abstract: This article critically investigates the limitations of the simulated annealing algorithm using probabilistic bits (pSA) in solving large-scale combinatorial optimization problems. The study begins with an in-depth analysis of the pSA process, focusing on the issues resul... | https://arxiv.org/abs/2601.15561 | Academic Papers | svg |
0ef8de5b9118179dba31437271e32127b7443fba850b68259fe0eb86a8828188 | 2026-01-23T00:00:00-05:00 | Verified polynomial-time reductions in Lean 4: formalizing the complexity of decision-relevant information | arXiv:2601.15571v1 Announce Type: new Abstract: We present a Lean 4 framework for polynomial-time reductions and complexity-theory proofs, and use it to formalize the complexity of identifying decision-relevant information. Problem: given a decision problem, which coordinates suffice to compute an optimal action? (SUFF... | https://arxiv.org/abs/2601.15571 | Academic Papers | svg |
f8de713f4413c604dd62bfdb6847fe498d2162773ad4b0205c8e72f014ed956c | 2026-01-23T00:00:00-05:00 | PromptHelper: A Prompt Recommender System for Encouraging Creativity in AI Chatbot Interactions | arXiv:2601.15575v1 Announce Type: new Abstract: Prompting is central to interaction with AI systems, yet many users struggle to explore alternative directions, articulate creative intent, or understand how variations in prompts shape model outputs. We introduce prompt recommender systems (PRS) as an interaction approac... | https://arxiv.org/abs/2601.15575 | Academic Papers | svg |
707d52e368bcd3328e59bf41b41a3367edad42540a77936a4f6d078072023df5 | 2026-01-23T00:00:00-05:00 | MapViT: A Two-Stage ViT-Based Framework for Real-Time Radio Quality Map Prediction in Dynamic Environments | arXiv:2601.15578v1 Announce Type: new Abstract: Recent advancements in mobile and wireless networks are unlocking the full potential of robotic autonomy, enabling robots to take advantage of ultra-low latency, high data throughput, and ubiquitous connectivity. However, for robots to navigate and operate seamlessly, eff... | https://arxiv.org/abs/2601.15578 | Academic Papers | svg |
a3917a8913e481464085dd6893d5a2ce872f195d4096f3439a3325bfc1e9a287 | 2026-01-23T00:00:00-05:00 | YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models | arXiv:2601.15588v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly deployed in real-world applications, safety guardrails are required to go beyond coarse-grained filtering and support fine-grained, interpretable, and adaptable risk assessment. However, existing solutions often rely on rap... | https://arxiv.org/abs/2601.15588 | Academic Papers | svg |
12d67be4dac919ae9c72e404793c4be4a664a6f3da9e3d400f6b97a0f46f0576 | 2026-01-23T00:00:00-05:00 | Deep Learning for Perishable Inventory Systems with Human Knowledge | arXiv:2601.15589v1 Announce Type: new Abstract: Managing perishable products with limited lifetimes is a fundamental challenge in inventory management, as poor ordering decisions can quickly lead to stockouts or excessive waste. We study a perishable inventory system with random lead times in which both the demand proc... | https://arxiv.org/abs/2601.15589 | Academic Papers | svg |
6769d4f051df5e553f9819e5371b39613a160944e164035668b305c57ee14b11 | 2026-01-23T00:00:00-05:00 | Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow | arXiv:2601.15593v1 Announce Type: new Abstract: Masked Diffusion Language Models (MDLMs) promise parallel token generation and arbitrary-order decoding, yet it remains unclear to what extent current models truly realize these capabilities. We characterize MDLM behavior along two dimensions -- parallelism strength and g... | https://arxiv.org/abs/2601.15593 | Academic Papers | svg |
371cc1f388ba22334a6dded2191bdac0349af87f2c1ddfbc8aa21f5109205b16 | 2026-01-23T00:00:00-05:00 | Blockchain-Based Spectrum Resource Securitization via Semi-Fungible Token-Lock | arXiv:2601.15594v1 Announce Type: new Abstract: As 6G networks evolve, spectrum assets require flexible, dynamic, and efficient utilization, motivating blockchain based spectrum securitization. Existing approaches based on ERC404 style hybrid token models rely on frequent minting and burning during asset transfers, whi... | https://arxiv.org/abs/2601.15594 | Academic Papers | svg |
3512aa0c91b93fa6e60dd3cab3e46eb8f2915fc26618e930c179ba362ab1215f | 2026-01-23T00:00:00-05:00 | Data-Free Privacy-Preserving for LLMs via Model Inversion and Selective Unlearning | arXiv:2601.15595v1 Announce Type: new Abstract: Large language models (LLMs) exhibit powerful capabilities but risk memorizing sensitive personally identifiable information (PII) from their training data, posing significant privacy concerns. While machine unlearning techniques aim to remove such data, they predominantl... | https://arxiv.org/abs/2601.15595 | Academic Papers | svg |
322ba90a81eec56c81af88b2012edd9f490e1793803f35e40805f5e890da5bc6 | 2026-01-23T00:00:00-05:00 | DeepASMR: LLM-Based Zero-Shot ASMR Speech Generation for Anyone of Any Voice | arXiv:2601.15596v1 Announce Type: new Abstract: While modern Text-to-Speech (TTS) systems achieve high fidelity for read-style speech, they struggle to generate Autonomous Sensory Meridian Response (ASMR), a specialized, low-intensity speech style essential for relaxation. The inherent challenges include ASMR's subtle,... | https://arxiv.org/abs/2601.15596 | Academic Papers | svg |
5ba6a6b8b024d63b813e6508ec58fcb39cab8a34248df50edf192180f7ad3c92 | 2026-01-23T00:00:00-05:00 | Neural Nonlinear Shrinkage of Covariance Matrices for Minimum Variance Portfolio Optimization | arXiv:2601.15597v1 Announce Type: new Abstract: This paper introduces a neural network-based nonlinear shrinkage estimator of covariance matrices for the purpose of minimum variance portfolio optimization. It is a hybrid approach that integrates statistical estimation with machine learning. Starting from the Ledoit-Wol... | https://arxiv.org/abs/2601.15597 | Academic Papers | svg |
3ac39fd10dd23e4d94cb62936f954a9b43f6ed7d5f07516b63bf328acc833137 | 2026-01-23T00:00:00-05:00 | Ternary Spiking Neural Networks Enhanced by Complemented Neurons and Membrane Potential Aggregation | arXiv:2601.15598v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) are promising energy-efficient models and powerful framworks of modeling neuron dynamics. However, existing binary spiking neurons exhibit limited biological plausibilities and low information capacity. Recently developed ternary spiking neu... | https://arxiv.org/abs/2601.15598 | Academic Papers | svg |
14f40fdc2cace5ec1a26526a879069cef5744c77a84b8dfd5b72d41afd9b5f45 | 2026-01-23T00:00:00-05:00 | Autonomous Business System via Neuro-symbolic AI | arXiv:2601.15599v1 Announce Type: new Abstract: Current business environments require organizations to continuously reconfigure cross-functional processes, yet enterprise systems are still organized around siloed departments, rigid workflows, and hard-coded automation. Meanwhile large language models (LLMs) excel at in... | https://arxiv.org/abs/2601.15599 | Academic Papers | svg |
45900e42cc6b7207323d3f6abee6f6541d3c409d361cb0bc072d0bff35346ee8 | 2026-01-23T00:00:00-05:00 | Tackling the Scaffolding Paradox: A Person-Centered Adaptive Robotic Interview Coach | arXiv:2601.15600v1 Announce Type: new Abstract: Job interview anxiety is a prevalent challenge among university students and can undermine both performance and confidence in high-stakes evaluative situations. Social robots have shown promise in reducing anxiety through emotional support, yet how such systems should bal... | https://arxiv.org/abs/2601.15600 | Academic Papers | svg |
c00df7309c53eca9aa9fe3ab8fc0f5a58bdc6247272dac00d15728b2a231eb07 | 2026-01-23T00:00:00-05:00 | ToxiTwitch: Toward Emote-Aware Hybrid Moderation for Live Streaming Platforms | arXiv:2601.15605v1 Announce Type: new Abstract: The rapid growth of live-streaming platforms such as Twitch has introduced complex challenges in moderating toxic behavior. Traditional moderation approaches, such as human annotation and keyword-based filtering, have demonstrated utility, but human moderators on Twitch c... | https://arxiv.org/abs/2601.15605 | Academic Papers | svg |
c93ef77e55fa5e97623247aba5da1746edfaba438ea78e7bd448429540f57ee8 | 2026-01-23T00:00:00-05:00 | Airflow Source Seeking on Small Quadrotors Using a Single Flow Sensor | arXiv:2601.15607v1 Announce Type: new Abstract: As environmental disasters happen more frequently and severely, seeking the source of pollutants or harmful particulates using plume tracking becomes even more important. Plume tracking on small quadrotors would allow these systems to operate around humans and fly in more... | https://arxiv.org/abs/2601.15607 | Academic Papers | svg |
e6aff58ec9de9ef29ec849369a7a41eaf2007019b0c48354eeed9600c36e9db2 | 2026-01-23T00:00:00-05:00 | When Sharpening Becomes Collapse: Sampling Bias and Semantic Coupling in RL with Verifiable Rewards | arXiv:2601.15609v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a central paradigm for turning large language models (LLMs) into reliable problem solvers, especially in logic-heavy domains. Despite its empirical success, it remains unclear whether RLVR elicits novel capabilities... | https://arxiv.org/abs/2601.15609 | Academic Papers | svg |
08766b9d68612cdb92d82cc1eb7aee1417cf81d684182560cf90aeb8231cd474 | 2026-01-23T00:00:00-05:00 | AION: Aerial Indoor Object-Goal Navigation Using Dual-Policy Reinforcement Learning | arXiv:2601.15614v1 Announce Type: new Abstract: Object-Goal Navigation (ObjectNav) requires an agent to autonomously explore an unknown environment and navigate toward target objects specified by a semantic label. While prior work has primarily studied zero-shot ObjectNav under 2D locomotion, extending it to aerial pla... | https://arxiv.org/abs/2601.15614 | Academic Papers | svg |
a7088eb50de22bc2f96d969a5a19fd012330eb4401c915e8b9567eb4d6a368b6 | 2026-01-23T00:00:00-05:00 | Region-aware Spatiotemporal Modeling with Collaborative Domain Generalization for Cross-Subject EEG Emotion Recognition | arXiv:2601.15615v1 Announce Type: new Abstract: Cross-subject EEG-based emotion recognition (EER) remains challenging due to strong inter-subject variability, which induces substantial distribution shifts in EEG signals, as well as the high complexity of emotion-related neural representations in both spatial organizati... | https://arxiv.org/abs/2601.15615 | Academic Papers | svg |
fd63a6e7084c3fc9ce424665c5a8884c4b7dce869a7b3471c97642c5d56810ba | 2026-01-23T00:00:00-05:00 | Closing the Gap on the Sample Complexity of 1-Identification | arXiv:2601.15620v1 Announce Type: new Abstract: 1-identification is a fundamental multi-armed bandit formulation on pure exploration. An agent aims to determine whether there exists a qualified arm whose mean reward is not less than a known threshold $\mu_0$, or to output \textsf{None} if it believes such an arm does n... | https://arxiv.org/abs/2601.15620 | Academic Papers | svg |
d6b9d07719523541b8a32aad4bcd453a6b2c21912312355c5d82089757d1a619 | 2026-01-23T00:00:00-05:00 | Qwen3-TTS Technical Report | arXiv:2601.15621v1 Announce Type: new Abstract: In this report, we present the Qwen3-TTS series, a family of advanced multilingual, controllable, robust, and streaming text-to-speech models. Qwen3-TTS supports state-of-the-art 3-second voice cloning and description-based control, allowing both the creation of entirely ... | https://arxiv.org/abs/2601.15621 | Academic Papers | svg |
43274ee177467ccc2b4aa0379987d7ddf3413497852fd7315c1cb36fc5a18809 | 2026-01-23T00:00:00-05:00 | Design, Modelling, and Control of Magnetic Ball Suspension System | arXiv:2601.15622v1 Announce Type: new Abstract: This paper presents the modeling, control design, and performance analysis of a Magnetic Ball Suspension System (MBSS), a nonlinear and inherently unstable electromechanical system used in various precision applications. The system's primary objective is to levitate a ste... | https://arxiv.org/abs/2601.15622 | Academic Papers | svg |
bf5251e8b189333d75e364b74f1048a352a2f10702ee089d28db354886146c31 | 2026-01-23T00:00:00-05:00 | Mapping Social Media User Behaviors in Reciprocity Space | arXiv:2601.15623v1 Announce Type: new Abstract: Social media users exhibit diverse behavioral patterns as platforms function simultaneously as information and friendship networks. We introduce a reciprocity-based framework mapping users onto two-dimensional space defined by bidirectional connection ratios. Analyzing 48... | https://arxiv.org/abs/2601.15623 | Academic Papers | svg |
2d112af23f43ecf5128696706f96da643013c30a46bf1146378cfbbf46dec211 | 2026-01-23T00:00:00-05:00 | Explainable Deepfake Detection with RL Enhanced Self-Blended Images | arXiv:2601.15624v1 Announce Type: new Abstract: Most prior deepfake detection methods lack explainable outputs. With the growing interest in multimodal large language models (MLLMs), researchers have started exploring their use in interpretable deepfake detection. However, a major obstacle in applying MLLMs to this tas... | https://arxiv.org/abs/2601.15624 | Academic Papers | svg |
010be16bb7437245bb91111be3b607a9f9ade6160ca6e8e47686b4970adf9f04 | 2026-01-23T00:00:00-05:00 | Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors | arXiv:2601.15625v1 Announce Type: new Abstract: Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: following a tool call error, smaller models often degenerate into repetitive invalid re-invocations, failing to interpret error feedback and self-correct. This brittl... | https://arxiv.org/abs/2601.15625 | Academic Papers | svg |
f0dbb6ca94eccd529f4e6bddd776edf5f71d4016eda6530ce98cf4f4440c17ab | 2026-01-23T00:00:00-05:00 | Bridging Qualitative Rubrics and AI: A Binary Question Framework for Criterion-Referenced Grading in Engineering | arXiv:2601.15626v1 Announce Type: new Abstract: PURPOSE OR GOAL: This study investigates how GenAI can be integrated with a criterion-referenced grading framework to improve the efficiency and quality of grading for mathematical assessments in engineering. It specifically explores the challenges demonstrators face with... | https://arxiv.org/abs/2601.15626 | Academic Papers | svg |
8c37ad480c770312fb5616a96d64d2fd800764896c167af805f1d24b13297737 | 2026-01-23T00:00:00-05:00 | CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models | arXiv:2601.15628v1 Announce Type: new Abstract: Whether Large Language Models (LLMs) truly possess human-like Theory of Mind (ToM) capabilities has garnered increasing attention. However, existing benchmarks remain largely restricted to narrow paradigms like false belief tasks, failing to capture the full spectrum of h... | https://arxiv.org/abs/2601.15628 | Academic Papers | svg |
02d361489f50484e040fc26137fc7f4c3f3f79e98b5127e048e6f799e101fe8c | 2026-01-23T00:00:00-05:00 | Agentic AI Governance and Lifecycle Management in Healthcare | arXiv:2601.15630v1 Announce Type: new Abstract: Healthcare organizations are beginning to embed agentic AI into routine workflows, including clinical documentation support and early-warning monitoring. As these capabilities diffuse across departments and vendors, health systems face agent sprawl, causing duplicated age... | https://arxiv.org/abs/2601.15630 | Academic Papers | svg |
572bf26caa202443c0dfe817d18e229385f503b1d537206bcb934dd2b8696648 | 2026-01-23T00:00:00-05:00 | Side-Channel Attacks on Open vSwitch | arXiv:2601.15632v1 Announce Type: new Abstract: Virtualization is widely adopted in cloud systems to manage resource sharing among users. A virtualized environment usually deploys a virtual switch within the host system to enable virtual machines to communicate with each other and with the physical network. The Open vS... | https://arxiv.org/abs/2601.15632 | Academic Papers | svg |
a75636bd47e1664e6c60361e71455ca0d624983470adf82c85b29dd829e5aad5 | 2026-01-23T00:00:00-05:00 | Advancing RT Core-Accelerated Fixed-Radius Nearest Neighbor Search | arXiv:2601.15633v1 Announce Type: new Abstract: In this work we introduce three ideas that can further improve particle FRNN physics simulations running on RT Cores; i) a real-time update/rebuild ratio optimizer for the bounding volume hierarchy (BVH) structure, ii) a new RT core use, with two variants, that eliminates... | https://arxiv.org/abs/2601.15633 | Academic Papers | svg |
ba0cfb38b76985ca0fbfa818d808e44b9759b7e28ee1b625b75803a45754b89e | 2026-01-23T00:00:00-05:00 | Community-Size Biases in Statistical Inference of Communities in Temporal Networks | arXiv:2601.15635v1 Announce Type: new Abstract: In the study of time-dependent (i.e., temporal) networks, researchers often examine the evolution of communities, which are sets of densely connected sets of nodes that are connected sparsely to other nodes. An increasingly prominent approach to studying community structu... | https://arxiv.org/abs/2601.15635 | Academic Papers | svg |
a0f0c7cdc81942b2021fc2b7b9c6e0d35fe9f7d75c7b91a3ae29171559e58873 | 2026-01-23T00:00:00-05:00 | A Class of Subadditive Information Measures and their Applications | arXiv:2601.15639v1 Announce Type: new Abstract: We introduce a two-parameter family of discrepancy measures, termed \emph{$(G,f)$-divergences}, obtained by applying a non-decreasing function $G$ to an $f$-divergence $D_f$. Building on Csisz\'ar's formulation of mutual $f$-information, we define a corresponding $(G,f)$-... | https://arxiv.org/abs/2601.15639 | Academic Papers | svg |
91cf9113e90e53c6801ce9830d2d31f06ebff8019d9aba3109aba85ea9048736 | 2026-01-23T00:00:00-05:00 | An Empirical Study on Ensemble-Based Transfer Learning Bayesian Optimisation with Mixed Variable Types | arXiv:2601.15640v1 Announce Type: new Abstract: Bayesian optimisation is a sample efficient method for finding a global optimum of expensive black-box objective functions. Historic datasets from related problems can be exploited to help improve performance of Bayesian optimisation by adapting transfer learning methods ... | https://arxiv.org/abs/2601.15640 | Academic Papers | svg |
57a20c0275a5aff1e5dabd4556ba5ce0472de57cc3fb2bf7a14106a0d5e1fff2 | 2026-01-23T00:00:00-05:00 | Generative AI-Empowered Semantic Twin Channel Model for ISAC | arXiv:2601.15642v1 Announce Type: new Abstract: Integrated sensing and communication (ISAC) increasingly exposes a gap in today's channel modeling. Efficient statistical models focus on coarse communication-centric metrics, and therefore miss the weak but critical multipath signatures for sensing, whereas deterministic... | https://arxiv.org/abs/2601.15642 | Academic Papers | svg |
136c66f035475a1c582e7559f3daf6dc702ff71334393363b7fec2462492adf0 | 2026-01-23T00:00:00-05:00 | Evolving Without Ending: Unifying Multimodal Incremental Learning for Continual Panoptic Perception | arXiv:2601.15643v1 Announce Type: new Abstract: Continual learning (CL) is a great endeavour in developing intelligent perception AI systems. However, the pioneer research has predominantly focus on single-task CL, which restricts the potential in multi-task and multimodal scenarios. Beyond the well-known issue of cata... | https://arxiv.org/abs/2601.15643 | Academic Papers | svg |
89fc254b060acba82e2de46c0c1e6bfd3dd2e26139f74b0e6e23e26c1ffe0e7c | 2026-01-23T00:00:00-05:00 | SuperOcc: Toward Cohesive Temporal Modeling for Superquadric-based Occupancy Prediction | arXiv:2601.15644v1 Announce Type: new Abstract: 3D occupancy prediction plays a pivotal role in the realm of autonomous driving, as it provides a comprehensive understanding of the driving environment. Most existing methods construct dense scene representations for occupancy prediction, overlooking the inherent sparsit... | https://arxiv.org/abs/2601.15644 | Academic Papers | svg |
f2bccbc0a734b81b98596a1861dd85e65241483561f62d2b1d6be49d923a7c73 | 2026-01-23T00:00:00-05:00 | Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation | arXiv:2601.15645v1 Announce Type: new Abstract: Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing studies have primarily evaluated confidence in single-turn, static settings, overlooking the coupling between confidence and co... | https://arxiv.org/abs/2601.15645 | Academic Papers | svg |
44546eda66f7f0dc8300ab3672f7a3f5b35d72174ad1e5f339f7ef76fb01c518 | 2026-01-23T00:00:00-05:00 | Predictive Coding and Information Bottleneck for Hallucination Detection in Large Language Models | arXiv:2601.15652v1 Announce Type: new Abstract: Hallucinations in Large Language Models (LLMs) -- generations that are plausible but factually unfaithful -- remain a critical barrier to high-stakes deployment. Current detection methods typically rely on computationally expensive external retrieval loops or opaque black... | https://arxiv.org/abs/2601.15652 | Academic Papers | svg |
87add076e36a15c832eb2594517b3ea762d3a469ec0db6609dbf6c4a1bf9b908 | 2026-01-23T00:00:00-05:00 | Event-VStream: Event-Driven Real-Time Understanding for Long Video Streams | arXiv:2601.15655v1 Announce Type: new Abstract: Real-time understanding of long video streams remains challenging for multimodal large language models (VLMs) due to redundant frame processing and rapid forgetting of past context. Existing streaming systems rely on fixed-interval decoding or cache pruning, which either ... | https://arxiv.org/abs/2601.15655 | Academic Papers | svg |
80e82ad841c46cb7d6b4c6dbf2ac7a420d5987befc7f2a7644f539c701ea2540 | 2026-01-23T00:00:00-05:00 | Reflective Motion and a Physical Canvas: Exploring Embodied Journaling in Virtual Reality | arXiv:2601.15656v1 Announce Type: new Abstract: In traditional journaling practices, authors express and process their thoughts by writing them down. We propose a somaesthetic-inspired alternative that uses the human body, rather than written words, as the medium of expression. We coin this embodied journaling, as peop... | https://arxiv.org/abs/2601.15656 | Academic Papers | svg |
48286d097bc1a3509cb4472a7067c9062f4c5e4067950d9dc1f35d97b05d5735 | 2026-01-23T00:00:00-05:00 | Integrating Knowledge Distillation Methods: A Sequential Multi-Stage Framework | arXiv:2601.15657v1 Announce Type: new Abstract: Knowledge distillation (KD) transfers knowledge from large teacher models to compact student models, enabling efficient deployment on resource constrained devices. While diverse KD methods, including response based, feature based, and relation based approaches, capture di... | https://arxiv.org/abs/2601.15657 | Academic Papers | svg |
95b1496da1f31a866918de493b8d8effe6f6f8971418d15c60fae7b595830106 | 2026-01-23T00:00:00-05:00 | TempoNet: Learning Realistic Communication and Timing Patterns for Network Traffic Simulation | arXiv:2601.15663v1 Announce Type: new Abstract: Realistic network traffic simulation is critical for evaluating intrusion detection systems, stress-testing network protocols, and constructing high-fidelity environments for cybersecurity training. While attack traffic can often be layered into training environments usin... | https://arxiv.org/abs/2601.15663 | Academic Papers | svg |
1ed2dfbf3c8642433e4b5ea61a6a3086930e169efdba77480e5728a6a5d42d56 | 2026-01-23T00:00:00-05:00 | Skywork UniPic 3.0: Unified Multi-Image Composition via Sequence Modeling | arXiv:2601.15664v1 Announce Type: new Abstract: The recent surge in popularity of Nano-Banana and Seedream 4.0 underscores the community's strong interest in multi-image composition tasks. Compared to single-image editing, multi-image composition presents significantly greater challenges in terms of consistency and qua... | https://arxiv.org/abs/2601.15664 | Academic Papers | svg |
34d010e3820bfad74dc528a3f59ea3551532ded7482d40fead90f25c4b6b5665 | 2026-01-23T00:00:00-05:00 | Impression Zombies: Characteristics Analysis and Classification of New Harmful Accounts on Social Media | arXiv:2601.15666v1 Announce Type: new Abstract: ``Impression Zombies'', a type of malicious account designed to artificially inflate engagement metrics, have recently emerged as a significant threat on X (formerly Twitter). These accounts disseminate a high volume of low-quality, irrelevant posts, which degrade the use... | https://arxiv.org/abs/2601.15666 | Academic Papers | svg |
ef84d3ee025d6218b31d76470fde2354b77ae780349c8eb501b2470a32a80ad9 | 2026-01-23T00:00:00-05:00 | EmotionThinker: Prosody-Aware Reinforcement Learning for Explainable Speech Emotion Reasoning | arXiv:2601.15668v1 Announce Type: new Abstract: Emotional information in speech plays a unique role in multimodal perception. However, current Speech Large Language Models (SpeechLLMs), similar to conventional speech emotion recognition (SER) systems, still treat emotion understanding as a simple classification problem... | https://arxiv.org/abs/2601.15668 | Academic Papers | svg |
2c972c35d41ee0b4fbac1e33dfe04a4fb63346cab131b4cb48cb40ce52161eda | 2026-01-23T00:00:00-05:00 | Dualformer: Time-Frequency Dual Domain Learning for Long-term Time Series Forecasting | arXiv:2601.15669v1 Announce Type: new Abstract: Transformer-based models, despite their promise for long-term time series forecasting (LTSF), suffer from an inherent low-pass filtering effect that limits their effectiveness. This issue arises due to undifferentiated propagation of frequency components across layers, ca... | https://arxiv.org/abs/2601.15669 | Academic Papers | svg |
7ee6aedac0567ecdd6ce5b79fc1027477568da7f409695f4c6c6412442bc7806 | 2026-01-23T00:00:00-05:00 | StreetDesignAI: A Multi-Persona Evaluation System for Inclusive Infrastructure Design | arXiv:2601.15671v1 Announce Type: new Abstract: Designing inclusive cycling infrastructure requires balancing competing needs of diverse user groups, yet designers often struggle to anticipate how different cyclists experience the same street. We investigate how persona-based multi-agent evaluation can support inclusiv... | https://arxiv.org/abs/2601.15671 | Academic Papers | svg |
40a2b2030f0f150a05539377018e2e365462af06c067c5cfd2c05adf4b986540 | 2026-01-23T00:00:00-05:00 | Enhancing guidance for missing data in diffusion-based sequential recommendation | arXiv:2601.15673v1 Announce Type: new Abstract: Contemporary sequential recommendation methods are becoming more complex, shifting from classification to a diffusion-guided generative paradigm. However, the quality of guidance in the form of user information is often compromised by missing data in the observed sequence... | https://arxiv.org/abs/2601.15673 | Academic Papers | svg |
08f160af7bc2b7b452c188cec44dd1b85c8057f3c79508f4e56a9ea886849a09 | 2026-01-23T00:00:00-05:00 | What Patients Really Ask: Exploring the Effect of False Assumptions in Patient Information Seeking | arXiv:2601.15674v1 Announce Type: new Abstract: Patients are increasingly using large language models (LLMs) to seek answers to their healthcare-related questions. However, benchmarking efforts in LLMs for question answering often focus on medical exam questions, which differ significantly in style and content from the... | https://arxiv.org/abs/2601.15674 | Academic Papers | svg |
72fa794aba9a6357f59baa1f80816f82196d4b2bc88e0ef8894d741323ae5e48 | 2026-01-23T00:00:00-05:00 | Bridging the Perception Gap: A Lightweight Coarse-to-Fine Architecture for Edge Audio Systems | arXiv:2601.15676v1 Announce Type: new Abstract: Deploying Audio-Language Models (Audio-LLMs) on edge infrastructure exposes a persistent tension between perception depth and computational efficiency. Lightweight local models tend to produce passive perception - generic summaries that miss the subtle evidence required f... | https://arxiv.org/abs/2601.15676 | Academic Papers | svg |
cbb1e6c0618924e0a09c697c07ee7b56789ed21babf4ec7cb1cc63f6185bb2fe | 2026-01-23T00:00:00-05:00 | Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systems | arXiv:2601.15678v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems integrate document retrieval with large language models and have been widely adopted. However, in privacy-related scenarios, RAG introduces a new privacy risk: adversaries can issue carefully crafted queries to exfiltrate sensi... | https://arxiv.org/abs/2601.15678 | Academic Papers | svg |
d1c32d037c19efd13ad00d2a3e467594dbfb65612fe6ba3ad3670e6449e8c6db | 2026-01-23T00:00:00-05:00 | Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats | arXiv:2601.15679v1 Announce Type: new Abstract: The rapid rise of autonomous AI systems and advancements in agent capabilities are introducing new risks due to reduced oversight of real-world interactions. Yet agent testing remains nascent and is still a developing science. As AI agents begin to be deployed globally, i... | https://arxiv.org/abs/2601.15679 | Academic Papers | svg |
8d8aa825b217429f718160725281140a6af36e1ff8c06735da1c2c7ad3a6b0d8 | 2026-01-23T00:00:00-05:00 | Consistency-Regularized GAN for Few-Shot SAR Target Recognition | arXiv:2601.15681v1 Announce Type: new Abstract: Few-shot recognition in synthetic aperture radar (SAR) imagery remains a critical bottleneck for real-world applications due to extreme data scarcity. A promising strategy involves synthesizing a large dataset with a generative adversarial network (GAN), pre-training a mo... | https://arxiv.org/abs/2601.15681 | Academic Papers | svg |
157b9fcf545c9c7cd5c5fca4fa27fbc794de607cf6dcd21767d6e1da30b593bc | 2026-01-23T00:00:00-05:00 | Tight Bounds for Gaussian Mean Estimation under Personalized Differential Privacy | arXiv:2601.15682v1 Announce Type: new Abstract: We study mean estimation for Gaussian distributions under \textit{personalized differential privacy} (PDP), where each record has its own privacy budget. PDP is commonly considered in two variants: \textit{bounded} and \textit{unbounded} PDP. In bounded PDP, the privacy b... | https://arxiv.org/abs/2601.15682 | Academic Papers | svg |
365857997cabb1fc792494f2545fa3b0b5539684b6b61af097078595ce02f1f3 | 2026-01-23T00:00:00-05:00 | Beyond Hard Writes and Rigid Preservation: Soft Recursive Least-Squares for Lifelong LLM Editing | arXiv:2601.15686v1 Announce Type: new Abstract: Model editing updates a pre-trained LLM with new facts or rules without re-training, while preserving unrelated behavior. In real deployment, edits arrive as long streams, and existing editors often face a plasticity-stability dilemma: locate-then-edit "hard writes" can a... | https://arxiv.org/abs/2601.15686 | Academic Papers | svg |
03d37f313ee19258514ee47420b085ec07693f9f5e28ff135728575c244df03d | 2026-01-23T00:00:00-05:00 | FARM: Field-Aware Resolution Model for Intelligent Trigger-Action Automation | arXiv:2601.15687v1 Announce Type: new Abstract: Trigger-Action Programming (TAP) platforms such as IFTTT and Zapier enable Web of Things (WoT) automation by composing event-driven rules across heterogeneous services. A TAP applet links a trigger to an action and must bind trigger outputs (ingredients) to action inputs ... | https://arxiv.org/abs/2601.15687 | Academic Papers | svg |
f80bdae85ecbeb773ab6131a1586c2f5f18c6f4c60525fd73cef07272beb926d | 2026-01-23T00:00:00-05:00 | Performance-guided Reinforced Active Learning for Object Detection | arXiv:2601.15688v1 Announce Type: new Abstract: Active learning (AL) strategies aim to train high-performance models with minimal labeling efforts, only selecting the most informative instances for annotation. Current approaches to evaluating data informativeness predominantly focus on the data's distribution or intrin... | https://arxiv.org/abs/2601.15688 | Academic Papers | svg |
24fa8f86d8dc246af633afcc56f0951fdd5906e827fdab8e1b3ab515a4b64ae1 | 2026-01-23T00:00:00-05:00 | From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models | arXiv:2601.15690v1 Announce Type: new Abstract: While Large Language Models (LLMs) show remarkable capabilities, their unreliability remains a critical barrier to deployment in high-stakes domains. This survey charts a functional evolution in addressing this challenge: the evolution of uncertainty from a passive diagno... | https://arxiv.org/abs/2601.15690 | Academic Papers | svg |
1dec427df9611dce30320e201f81c1fa0c33d30e6fd5f5f917452bbf14df5781 | 2026-01-23T00:00:00-05:00 | Balancing Security and Privacy: The Pivotal Role of AI in Modern Healthcare Systems | arXiv:2601.15697v1 Announce Type: new Abstract: As digital threats continue to grow, organizations must find ways to enhance security while protecting user privacy. This paper explores how artificial intelligence (AI) plays a crucial role in achieving this balance. AI technologies can improve security by detecting thre... | https://arxiv.org/abs/2601.15697 | Academic Papers | svg |
5465a1294f86512c5d93507842987fc77d459bdbbb2a4d5a68b5cca706f67858 | 2026-01-23T00:00:00-05:00 | Beyond Visual Safety: Jailbreaking Multimodal Large Language Models for Harmful Image Generation via Semantic-Agnostic Inputs | arXiv:2601.15698v1 Announce Type: new Abstract: The rapid advancement of Multimodal Large Language Models (MLLMs) has introduced complex security challenges, particularly at the intersection of textual and visual safety. While existing schemes have explored the security vulnerabilities of MLLMs, the investigation into ... | https://arxiv.org/abs/2601.15698 | Academic Papers | svg |
f6628459dc72f63d27eb3b2abdf3740a2f31226bcf845d8cbecd55d750acc179 | 2026-01-23T00:00:00-05:00 | Agentic Uncertainty Quantification | arXiv:2601.15703v1 Announce Type: new Abstract: Although AI agents have demonstrated impressive capabilities in long-horizon reasoning, their reliability is severely hampered by the ``Spiral of Hallucination,'' where early epistemic errors propagate irreversibly. Existing methods face a dilemma: uncertainty quantificat... | https://arxiv.org/abs/2601.15703 | Academic Papers | svg |
ee69b8e161f472e371619c84f7a49cff89adb2e74b78cb28eebfb608e5f7bce1 | 2026-01-23T00:00:00-05:00 | Enhanced LULC Segmentation via Lightweight Model Refinements on ALOS-2 SAR Data | arXiv:2601.15705v1 Announce Type: new Abstract: This work focuses on national-scale land-use/land-cover (LULC) semantic segmentation using ALOS-2 single-polarization (HH) SAR data over Japan, together with a companion binary water detection task. Building on SAR-W-MixMAE self-supervised pretraining [1], we address comm... | https://arxiv.org/abs/2601.15705 | Academic Papers | svg |
b034b7776194f202bcc4a48132e3289852db823235e4d32595f416cd43663d2e | 2026-01-23T00:00:00-05:00 | Improving Methodologies for LLM Evaluations Across Global Languages | arXiv:2601.15706v1 Announce Type: new Abstract: As frontier AI models are deployed globally, it is essential that their behaviour remains safe and reliable across diverse linguistic and cultural contexts. To examine how current model safeguards hold up in such settings, participants from the International Network for A... | https://arxiv.org/abs/2601.15706 | Academic Papers | svg |
99813d7a6ef4b545fa890872fee875a3683675f5d9103ea88f7f5d6529582fdd | 2026-01-23T00:00:00-05:00 | D-Optimality-Guided Reinforcement Learning for Efficient Open-Loop Calibration of a 3-DOF Ankle Rehabilitation Robot | arXiv:2601.15707v1 Announce Type: new Abstract: Accurate alignment of multi-degree-of-freedom rehabilitation robots is essential for safe and effective patient training. This paper proposes a two-stage calibration framework for a self-designed three-degree-of-freedom (3-DOF) ankle rehabilitation robot. First, a Kroneck... | https://arxiv.org/abs/2601.15707 | Academic Papers | svg |
fa0afddb49dec4a9e8ce00fb41478d52f57b5817ab6141bb132b5e7c3ba39fd8 | 2026-01-23T00:00:00-05:00 | Persona Switch: Mixing Distinct Perspectives in Decoding Time | arXiv:2601.15708v1 Announce Type: new Abstract: Role-play prompting is known to steer the behavior of language models by injecting a persona into the prompt, improving their zero-shot reasoning capabilities. However, such improvements are inconsistent across different tasks or instances. This inconsistency suggests tha... | https://arxiv.org/abs/2601.15708 | Academic Papers | svg |
e6c5f1eea124b097a35f514aca889b8b07fb1a2fa5706717e81fce4df30e1a17 | 2026-01-23T00:00:00-05:00 | AgentSM: Semantic Memory for Agentic Text-to-SQL | arXiv:2601.15709v1 Announce Type: new Abstract: Recent advances in LLM-based Text-to-SQL have achieved remarkable gains on public benchmarks such as BIRD and Spider. Yet, these systems struggle to scale in realistic enterprise settings with large, complex schemas, diverse SQL dialects, and expensive multi-step reasonin... | https://arxiv.org/abs/2601.15709 | Academic Papers | svg |
bd824d62857c0602e4aa27ec913047dc7c8f94f3e0f990adfda3e46a2c03c6ee | 2026-01-23T00:00:00-05:00 | FlexLLM: Composable HLS Library for Flexible Hybrid LLM Accelerator Design | arXiv:2601.15710v1 Announce Type: new Abstract: We present FlexLLM, a composable High-Level Synthesis (HLS) library for rapid development of domain-specific LLM accelerators. FlexLLM exposes key architectural degrees of freedom for stage-customized inference, enabling hybrid designs that tailor temporal reuse and spati... | https://arxiv.org/abs/2601.15710 | Academic Papers | svg |
4a15d042506ae47f8d99f3437098d5ed2e324649dd367e854bc1ad614cb2002c | 2026-01-23T00:00:00-05:00 | Zero-Shot Product Attribute Labeling with Vision-Language Models: A Three-Tier Evaluation Framework | arXiv:2601.15711v1 Announce Type: new Abstract: Fine-grained attribute prediction is essential for fashion retail applications including catalog enrichment, visual search, and recommendation systems. Vision-Language Models (VLMs) offer zero-shot prediction without task-specific training, yet their systematic evaluation... | https://arxiv.org/abs/2601.15711 | Academic Papers | svg |
fcffce547c97953a16013565a9f0b50dd1521c2e1cb589a1f91cb7a01a34d0cd | 2026-01-23T00:00:00-05:00 | Even GPT-5.2 Can't Count to Five: The Case for Zero-Error Horizons in Trustworthy LLMs | arXiv:2601.15714v1 Announce Type: new Abstract: We propose Zero-Error Horizon (ZEH) for trustworthy LLMs, which represents the maximum range that a model can solve without any errors. While ZEH itself is simple, we demonstrate that evaluating the ZEH of state-of-the-art LLMs yields abundant insights. For example, by ev... | https://arxiv.org/abs/2601.15714 | Academic Papers | svg |
ba7d47cbbc20d7710f473d06ee08697143a0351be77490c99efc96a97f677f75 | 2026-01-23T00:00:00-05:00 | Dancing in Chains: Strategic Persuasion in Academic Rebuttal via Theory of Mind | arXiv:2601.15715v1 Announce Type: new Abstract: Although artificial intelligence (AI) has become deeply integrated into various stages of the research workflow and achieved remarkable advancements, academic rebuttal remains a significant and underexplored challenge. This is because rebuttal is a complex process of stra... | https://arxiv.org/abs/2601.15715 | Academic Papers | svg |
8376b70b30f445cff283ce654e7742554c569ebbd6b90d2bc67420d889c16dc5 | 2026-01-23T00:00:00-05:00 | zkFinGPT: Zero-Knowledge Proofs for Financial Generative Pre-trained Transformers | arXiv:2601.15716v1 Announce Type: new Abstract: Financial Generative Pre-trained Transformers (FinGPT) with multimodal capabilities are now being increasingly adopted in various financial applications. However, due to the intellectual property of model weights and the copyright of training corpus and benchmarking quest... | https://arxiv.org/abs/2601.15716 | Academic Papers | svg |
ce7a35791d34f101037e8c0b7fb57342b6eff2d5a1fb23286265a8fe68fc45da | 2026-01-23T00:00:00-05:00 | Investigation of the Generalisation Ability of Genetic Programming-evolved Scheduling Rules in Dynamic Flexible Job Shop Scheduling | arXiv:2601.15717v1 Announce Type: new Abstract: Dynamic Flexible Job Shop Scheduling (DFJSS) is a complex combinatorial optimisation problem that requires simultaneous machine assignment and operation sequencing decisions in dynamic production environments. Genetic Programming (GP) has been widely applied to automatica... | https://arxiv.org/abs/2601.15717 | Academic Papers | svg |
66380d3ecb32bc77e2081ca3ac25684387806f59c9f35efdfedc172c0966950b | 2026-01-23T00:00:00-05:00 | U3-xi: Pushing the Boundaries of Speaker Recognition via Incorporating Uncertainty | arXiv:2601.15719v1 Announce Type: new Abstract: An utterance-level speaker embedding is typically obtained by aggregating a sequence of frame-level representations. However, in real-world scenarios, individual frames encode not only speaker-relevant information but also various nuisance factors. As a result, different ... | https://arxiv.org/abs/2601.15719 | Academic Papers | svg |
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