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47b825f3095991c214d726926a67dbb4b3aa70fb07f97bdcfa552e5e5694abaa | 2026-01-20T00:00:00 | Fossil-fuel phase out is not enough: countries must remove atmospheric carbon | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00211-w | https://www.nature.com/articles/d41586-026-00211-w | Academic Papers | svg |
6614c58cfb6f9a729c38367f91211998bb64974458a44d2c828588b4c0b2b574 | 2026-01-20T00:00:00 | Mistaken identity and the psychology of human recognition | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00190-y | https://www.nature.com/articles/d41586-026-00190-y | Academic Papers | svg |
72d21de2b5da9929d424ca5930f5072091257e0ee731dda7236cecb3aba3b05a | 2026-01-20T00:00:00 | US Congress set to reject Trump’s sweeping science budget cuts | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00163-1 | https://www.nature.com/articles/d41586-026-00163-1 | Academic Papers | svg |
dec092ffbced0ffa9725ad60f18a6fed65a01b7180da0d41d5f945db4422b8e7 | 2026-01-20T00:00:00 | Trump one year on: How six US researchers plan to protect science amid chaos and cuts | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00090-1 | https://www.nature.com/articles/d41586-026-00090-1 | Academic Papers | svg |
cbf00e37a398f88631a1b82a9bd82c342d3c0495222be567f7307dd5de0be2bb | 2026-01-20T00:00:00 | The US is quitting 66 global agencies: what does it mean for science? | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00102-0 | https://www.nature.com/articles/d41586-026-00102-0 | Academic Papers | svg |
bbf571eb2955791480733dcc2990cf17c4f2b7833f49adc3bf9af15ec69966aa | 2026-01-20T00:00:00 | US science after a year of Trump: what has been lost and what remains | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00088-9 | https://www.nature.com/articles/d41586-026-00088-9 | Academic Papers | svg |
1b996701cd20e0dd2a32aea31458806f7e8d332e2b0ecfe100604f590e831c3d | 2026-01-20T00:00:00 | ‘Shattered’: US scientists speak out about how Trump policies disrupted their careers | Nature, Published online: 20 January 2026; doi:10.1038/d41586-026-00091-0 | https://www.nature.com/articles/d41586-026-00091-0 | Academic Papers | svg |
d26e680d6bdbce6a47b98b98597205d4b9cecc35ffb48a0ff758262a919789c8 | 2026-01-19T00:00:00 | Collective intelligence for AI-assisted chemical synthesis | Nature, Published online: 19 January 2026; doi:10.1038/s41586-026-10131-4 | https://www.nature.com/articles/s41586-026-10131-4 | Academic Papers | svg |
51a83b2e9258f2f9853640f89c5736413d46ae7e62c9d3063039a96aaa63a7f1 | 2026-01-19T00:00:00 | Publisher Correction: A fault-tolerant neutral-atom architecture for universal quantum computation | Nature, Published online: 19 January 2026; doi:10.1038/s41586-026-10108-3 | https://www.nature.com/articles/s41586-026-10108-3 | Academic Papers | svg |
4c618c7e6cd9f0c845e76a77cdfd7fe8569e2328735aefc75df8053778da4930 | 2026-01-19T00:00:00 | Editorial Expression of Concern: <i>En passant</i> neurotrophic action of an intermediate axonal target in the developing mammalian CNS | Nature, Published online: 19 January 2026; doi:10.1038/s41586-025-10080-4 | https://www.nature.com/articles/s41586-025-10080-4 | Academic Papers | svg |
f2d7b271b37ce3291f7dd358662471d9070fde0eb21077953525621707a7f5ea | 2026-01-19T00:00:00 | Author Correction: An autonomous laboratory for the accelerated synthesis of inorganic materials | Nature, Published online: 19 January 2026; doi:10.1038/s41586-025-09992-y | https://www.nature.com/articles/s41586-025-09992-y | Academic Papers | svg |
4071db67aa41b354aa1fba6a883db5a68603c63257831451b962c42a6166855c | 2026-01-19T00:00:00 | Floating science stations: my month on a research vessel looking after buoys | Nature, Published online: 19 January 2026; doi:10.1038/d41586-026-00189-5 | https://www.nature.com/articles/d41586-026-00189-5 | Academic Papers | svg |
bccfb78b8b98e662ae52d8da00ad2e24eb252264ec23111d22db564dc7aec528 | 2026-01-19T00:00:00 | ‘Greed is the iron cage of our times’ — why nationalism is here to stay | Nature, Published online: 19 January 2026; doi:10.1038/d41586-026-00186-8 | https://www.nature.com/articles/d41586-026-00186-8 | Academic Papers | svg |
cfcba1d5f9b7eded7571f0a795316c783277204f49ed4512047e9e8e0ebb4935 | 2026-01-19T00:00:00 | Can ‘toxic masculinity’ be measured? Scientists try to quantify controversial term | Nature, Published online: 19 January 2026; doi:10.1038/d41586-026-00144-4 | https://www.nature.com/articles/d41586-026-00144-4 | Academic Papers | svg |
b6ea0522030107eb4bf672f056503945e761a54af63226b845e8045e5c350ac7 | 2026-01-19T00:00:00 | Forget formalism: mathematics was built on infighting and emotional turmoil | Nature, Published online: 19 January 2026; doi:10.1038/d41586-026-00187-7 | https://www.nature.com/articles/d41586-026-00187-7 | Academic Papers | svg |
6cc57c4f5dc05bee74e1734ca20b8dd0b47b5a8b54b1aacaec29468f27f17740 | 2026-01-19T00:00:00 | Daily briefing: Gifted dogs have word-learning skills on a par with human toddlers | Nature, Published online: 19 January 2026; doi:10.1038/d41586-026-00213-8 | https://www.nature.com/articles/d41586-026-00213-8 | Academic Papers | svg |
0233e0f2f2290c1fde0c6b187e39daec9ff2f7d31923e9a739f1ca5d0078fd1b | 2026-01-19T00:00:00 | I’m going to halve my publication output. You should consider slow science, too | Nature, Published online: 19 January 2026; doi:10.1038/d41586-025-04061-w | https://www.nature.com/articles/d41586-025-04061-w | Academic Papers | svg |
495f54e274c4b7b3f02ac405d8b04b990a78d98074626c5e268198362659a22b | 2026-01-16T00:00:00 | Daily briefing: Symbols on ancient pottery could be earliest evidence of mathematics | Nature, Published online: 16 January 2026; doi:10.1038/d41586-026-00201-y | https://www.nature.com/articles/d41586-026-00201-y | Academic Papers | svg |
2e0c502be812b88dbe9cdf4bbfca1a274afa28e70920ee6a06ef85ce5e060d7c | 2026-01-21T00:00:00-05:00 | SynQP: A Framework and Metrics for Evaluating the Quality and Privacy Risk of Synthetic Data | arXiv:2601.12124v1 Announce Type: new Abstract: The use of synthetic data in health applications raises privacy concerns, yet the lack of open frameworks for privacy evaluations has slowed its adoption. A major challenge is the absence of accessible benchmark datasets for evaluating privacy risks, due to difficulties i... | https://arxiv.org/abs/2601.12124 | Academic Papers | svg |
5f5a59a3a6931e72aebe1598b66edc3eb8f6c24cb1bbe2a35de472a35d529ab9 | 2026-01-21T00:00:00-05:00 | UniMo: Unified Motion Generation and Understanding with Chain of Thought | arXiv:2601.12126v1 Announce Type: new Abstract: Existing 3D human motion generation and understanding methods often exhibit limited interpretability, restricting effective mutual enhancement between these inherently related tasks. While current unified frameworks based on large language models (LLMs) leverage linguisti... | https://arxiv.org/abs/2601.12126 | Academic Papers | svg |
86ab09de93d08e481199ebf3a17cfb5fcf968d9afe4f3be55c69e93e7d7f0aaf | 2026-01-21T00:00:00-05:00 | SolarGPT-QA: A Domain-Adaptive Large Language Model for Educational Question Answering in Space Weather and Heliophysics | arXiv:2601.12131v1 Announce Type: new Abstract: Solar activity, including solar flares, coronal mass ejections (CMEs), and geomagnetic storms, can significantly impact satellites, aviation, power grids, data centers, and space missions. Extreme solar events can cause substantial economic damage if not predicted in adva... | https://arxiv.org/abs/2601.12131 | Academic Papers | svg |
83a5c8281d1a1065843d61a2b195bfc715c103fee3bb741a8971753cbdaba195 | 2026-01-21T00:00:00-05:00 | Bengali Text Classification: An Evaluation of Large Language Model Approaches | arXiv:2601.12132v1 Announce Type: new Abstract: Bengali text classification is a Significant task in natural language processing (NLP), where text is categorized into predefined labels. Unlike English, Bengali faces challenges due to the lack of extensive annotated datasets and pre-trained language models. This study e... | https://arxiv.org/abs/2601.12132 | Academic Papers | svg |
fc85b2ab0b3edecb3b49912de190ecd173fef1725f0569a5b2d60f182c86abba | 2026-01-21T00:00:00-05:00 | Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative Learning | arXiv:2601.12134v1 Announce Type: new Abstract: As AI assistance becomes embedded in programming practice, researchers have increasingly examined how these systems help learners generate code and work more efficiently. However, these studies often position AI as a replacement for human collaboration and overlook the so... | https://arxiv.org/abs/2601.12134 | Academic Papers | svg |
368a72f476f145ab0eb6b3be0d8060cbb37f69c86dba86770229cd003c8c62be | 2026-01-21T00:00:00-05:00 | CoSMeTIC: Zero-Knowledge Computational Sparse Merkle Trees with Inclusion-Exclusion Proofs for Clinical Research | arXiv:2601.12136v1 Announce Type: new Abstract: Analysis of clinical data is a cornerstone of biomedical research with applications in areas such as genomic testing and response characterization of therapeutic drugs. Maintaining strict privacy controls is essential because such data typically contains personally identi... | https://arxiv.org/abs/2601.12136 | Academic Papers | svg |
038244204fdb9c38f96010975de4caeb57079e6cdedca2dc6e5dbba81717b732 | 2026-01-21T00:00:00-05:00 | EMoE: Eigenbasis-Guided Routing for Mixture-of-Experts | arXiv:2601.12137v1 Announce Type: new Abstract: The relentless scaling of deep learning models has led to unsustainable computational demands, positioning Mixture-of-Experts (MoE) architectures as a promising path towards greater efficiency. However, MoE models are plagued by two fundamental challenges: 1) a load imbal... | https://arxiv.org/abs/2601.12137 | Academic Papers | svg |
445724db67b79726eb21dedb3604b033ffed8e72a815676c50d959075ac50863 | 2026-01-21T00:00:00-05:00 | DriveSafe: A Hierarchical Risk Taxonomy for Safety-Critical LLM-Based Driving Assistants | arXiv:2601.12138v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into vehicle-based digital assistants, where unsafe, ambiguous, or legally incorrect responses can lead to serious safety, ethical, and regulatory consequences. Despite growing interest in LLM safety, existing taxon... | https://arxiv.org/abs/2601.12138 | Academic Papers | svg |
839a7c93c091d27c5fa6399610f14b6fb8e541f6a08a7617613618e133aea437 | 2026-01-21T00:00:00-05:00 | TIDE: A Trace-Informed Depth-First Exploration for Planning with Temporally Extended Goals | arXiv:2601.12141v1 Announce Type: new Abstract: Task planning with temporally extended goals (TEGs) is a critical challenge in AI and robotics, enabling agents to achieve complex sequences of objectives over time rather than addressing isolated, immediate tasks. Linear Temporal Logic on finite traces (LTLf ) provides a... | https://arxiv.org/abs/2601.12141 | Academic Papers | svg |
a6f99938c6084692e29805f8b80973ab8f0c271582c481460f154a1df5ad856b | 2026-01-21T00:00:00-05:00 | Neural Process-Based Reactive Controller for Autonomous Racing | arXiv:2601.12143v1 Announce Type: new Abstract: Attention-based neural architectures have become central to state-of-the-art methods in real-time nonlinear control. As these data-driven models continue to be integrated into increasingly safety-critical domains, ensuring statistically grounded and provably safe decision... | https://arxiv.org/abs/2601.12143 | Academic Papers | svg |
12135c426ccb4655c478f61fee33eb237d7c89a82d05126b21664af14b99e912 | 2026-01-21T00:00:00-05:00 | Threshold Differential Attention for Sink-Free, Ultra-Sparse, and Non-Dispersive Language Modeling | arXiv:2601.12145v1 Announce Type: new Abstract: Softmax attention struggles with long contexts due to structural limitations: the strict sum-to-one constraint forces attention sinks on irrelevant tokens, and probability mass disperses as sequence lengths increase. We tackle these problems with Threshold Differential At... | https://arxiv.org/abs/2601.12145 | Academic Papers | svg |
7d57a69b1bafa609c01b8ec45e71d07cfacf2552176ce8e7b22f69cafbaa0e49 | 2026-01-21T00:00:00-05:00 | From LLMs to Agents in Programming: The Impact of Providing an LLM with a Compiler | arXiv:2601.12146v1 Announce Type: new Abstract: Large Language Models have demonstrated a remarkable capability in natural language and program generation and software development. However, the source code generated by the LLMs does not always meet quality requirements and may fail to compile. Therefore, many studies e... | https://arxiv.org/abs/2601.12146 | Academic Papers | svg |
0e4ce11b1caf84b9c8dcdbedc0f4ceea9354f31bcd28f6d1dc732086d72247d7 | 2026-01-21T00:00:00-05:00 | Segment and Matte Anything in a Unified Model | arXiv:2601.12147v1 Announce Type: new Abstract: Segment Anything (SAM) has recently pushed the boundaries of segmentation by demonstrating zero-shot generalization and flexible prompting after training on over one billion masks. Despite this, its mask prediction accuracy often falls short of the precision required in r... | https://arxiv.org/abs/2601.12147 | Academic Papers | svg |
8aa3c3b10851fba335ad4b61affe39a3d57f856a31e522e6fed20e0edee52f06 | 2026-01-21T00:00:00-05:00 | Many Hands Make Light Work: An LLM-based Multi-Agent System for Detecting Malicious PyPI Packages | arXiv:2601.12148v1 Announce Type: new Abstract: Malicious code in open-source repositories such as PyPI poses a growing threat to software supply chains. Traditional rule-based tools often overlook the semantic patterns in source code that are crucial for identifying adversarial components. Large language models (LLMs)... | https://arxiv.org/abs/2601.12148 | Academic Papers | svg |
3d93ce93e5a236b3c8d6b04fed9b63fce88fbdc339936084e4f5d764da0371c5 | 2026-01-21T00:00:00-05:00 | Principal Component Analysis-Based Terahertz Self-Supervised Denoising and Deblurring Deep Neural Networks | arXiv:2601.12149v1 Announce Type: new Abstract: Terahertz (THz) systems inherently introduce frequency-dependent degradation effects, resulting in low-frequency blurring and high-frequency noise in amplitude images. Conventional image processing techniques cannot simultaneously address both issues, and manual intervent... | https://arxiv.org/abs/2601.12149 | Academic Papers | svg |
5e4a91a52ed4f5392a5fb4be686654ce822ee9c51de6b5045c223585c8b0fdc6 | 2026-01-21T00:00:00-05:00 | Enhanced Diagnostic Performance via Large-Resolution Inference Optimization for Pathology Foundation Models | arXiv:2601.12150v1 Announce Type: new Abstract: Despite their prominent performance on tasks such as ROI classification and segmentation, many pathology foundation models remain constrained by a specific input size e.g. 224 x 224, creating substantial inefficiencies when applied to whole-slide images (WSIs), which span... | https://arxiv.org/abs/2601.12150 | Academic Papers | svg |
43022866ca9e3f62e08cbc23971162006d4a7ffb4b77395cddddcba304c2aca4 | 2026-01-21T00:00:00-05:00 | Who Owns Creativity and Who Does the Work? Trade-offs in LLM-Supported Research Ideation | arXiv:2601.12152v1 Announce Type: new Abstract: LLM-based agents offer new potential to accelerate science and reshape research work. However, the quality of researcher contributions can vary significantly depending on human ability to steer agent behaviors. How can we best use these tools to augment scientific creativ... | https://arxiv.org/abs/2601.12152 | Academic Papers | svg |
7c5a1b3042f3715f9d29ec854b253e6ae0527aee46912a49249fbb1b60e8a410 | 2026-01-21T00:00:00-05:00 | Analyzing Cancer Patients' Experiences with Embedding-based Topic Modeling and LLMs | arXiv:2601.12154v1 Announce Type: new Abstract: This study investigates the use of neural topic modeling and LLMs to uncover meaningful themes from patient storytelling data, to offer insights that could contribute to more patient-oriented healthcare practices. We analyze a collection of transcribed interviews with can... | https://arxiv.org/abs/2601.12154 | Academic Papers | svg |
98d7877819bfbc164bf259320abf0755946e799c581f310c2e0343617e6fa24a | 2026-01-21T00:00:00-05:00 | Inverse Rendering for High-Genus 3D Surface Meshes from Multi-view Images with Persistent Homology Priors | arXiv:2601.12155v1 Announce Type: new Abstract: Reconstructing 3D objects from images is inherently an ill-posed problem due to ambiguities in geometry, appearance, and topology. This paper introduces collaborative inverse rendering with persistent homology priors, a novel strategy that leverages topological constraint... | https://arxiv.org/abs/2601.12155 | Academic Papers | svg |
aceb93f7090c675aed026f0b85af612efc34d86a6b3616549933533e0c2c9a83 | 2026-01-21T00:00:00-05:00 | Biological Intuition on Digital Hardware: An RTL Implementation of Poisson-Encoded SNNs for Static Image Classification | arXiv:2601.12156v1 Announce Type: new Abstract: The deployment of Artificial Intelligence on edge devices (TinyML) is often constrained by the high power consumption and latency associated with traditional Artificial Neural Networks (ANNs) and their reliance on intensive Matrix-Multiply (MAC) operations. Neuromorphic c... | https://arxiv.org/abs/2601.12156 | Academic Papers | svg |
eeb1cea37645a5214756b3f106f794da13a3e1db39401cfbe7c7538506be41f7 | 2026-01-21T00:00:00-05:00 | Streaming Operator Inference for Model Reduction of Large-Scale Dynamical Systems | arXiv:2601.12161v1 Announce Type: new Abstract: Projection-based model reduction enables efficient simulation of complex dynamical systems by constructing low-dimensional surrogate models from high-dimensional data. The Operator Inference (OpInf) approach learns such reduced surrogate models through a two-step process:... | https://arxiv.org/abs/2601.12161 | Academic Papers | svg |
086022e362e01357a2332be6ea71f6abcd5d242bf0d6bcea1bb5011741dd19b2 | 2026-01-21T00:00:00-05:00 | The Language You Ask In: Language-Conditioned Ideological Divergence in LLM Analysis of Contested Political Documents | arXiv:2601.12164v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed as analytical tools across multilingual contexts, yet their outputs may carry systematic biases conditioned by the language of the prompt. This study presents an experimental comparison of LLM-generated political anal... | https://arxiv.org/abs/2601.12164 | Academic Papers | svg |
d523d87f0685534888f6b3c97173f07377cca943437222a00ec5115b523d11c9 | 2026-01-21T00:00:00-05:00 | Learning Legged MPC with Smooth Neural Surrogates | arXiv:2601.12169v1 Announce Type: new Abstract: Deep learning and model predictive control (MPC) can play complementary roles in legged robotics. However, integrating learned models with online planning remains challenging. When dynamics are learned with neural networks, three key difficulties arise: (1) stiff transiti... | https://arxiv.org/abs/2601.12169 | Academic Papers | svg |
35bfe1ff893daa4d0cfbc6e0070bc68a00e92a6a9c7377c1d2438462e591e789 | 2026-01-21T00:00:00-05:00 | Federated Learning for the Design of Parametric Insurance Indices under Heterogeneous Renewable Production Losses | arXiv:2601.12178v1 Announce Type: new Abstract: We propose a federated learning framework for the calibration of parametric insurance indices under heterogeneous renewable energy production losses. Producers locally model their losses using Tweedie generalized linear models and private data, while a common index is lea... | https://arxiv.org/abs/2601.12178 | Academic Papers | svg |
261556517a374fb4e989282cf8c2a7ccc87688bf03b867f3b02e6ecc361bccb7 | 2026-01-21T00:00:00-05:00 | Tolerance Principle and Small Language Model Learning | arXiv:2601.12179v1 Announce Type: new Abstract: Modern language models like GPT-3, BERT, and LLaMA require massive training data, yet with sufficient training they reliably learn to distinguish grammatical from ungrammatical sentences. Children aged as young as 14 months already have the capacity to learn abstract gram... | https://arxiv.org/abs/2601.12179 | Academic Papers | svg |
fa118e54a35aa7692d2c06455c977b21cd4ba2f270ce69cbe509cb81d198a86b | 2026-01-21T00:00:00-05:00 | VidTune: Creating Video Soundtracks with Generative Music and Contextual Thumbnails | arXiv:2601.12180v1 Announce Type: new Abstract: Music shapes the tone of videos, yet creators often struggle to find soundtracks that match their video's mood and narrative. Recent text-to-music models let creators generate music from text prompts, but our formative study (N=8) shows creators struggle to construct dive... | https://arxiv.org/abs/2601.12180 | Academic Papers | svg |
be6d1530ecf26768fd190cd198e77950eadc35a8786062c87329c7bf9fb3bdaa | 2026-01-21T00:00:00-05:00 | Negotiating Digital Identities with AI Companions: Motivations, Strategies, and Emotional Outcomes | arXiv:2601.12181v1 Announce Type: new Abstract: AI companions enable deep emotional relationships by engaging a user's sense of identity, but they also pose risks like unhealthy emotional dependence. Mitigating these risks requires first understanding the underlying process of identity construction and negotiation with... | https://arxiv.org/abs/2601.12181 | Academic Papers | svg |
2132431e39cdc3e79ef09e063632b44f03db17b55b545048fcff2fa9b4b532ad | 2026-01-21T00:00:00-05:00 | Aletheia: What Makes RLVR For Code Verifiers Tick? | arXiv:2601.12186v1 Announce Type: new Abstract: Multi-domain thinking verifiers trained via Reinforcement Learning from Verifiable Rewards (RLVR) are a prominent fixture of the Large Language Model (LLM) post-training pipeline, owing to their ability to robustly rate and rerank model outputs. However, the adoption of s... | https://arxiv.org/abs/2601.12186 | Academic Papers | svg |
fe4a4cee132c648203bc2ebf3c9eccea00b105f7533f1153a018ff51cc7c7606 | 2026-01-21T00:00:00-05:00 | VIRTUE: Versatile Video Retrieval Through Unified Embeddings | arXiv:2601.12193v1 Announce Type: new Abstract: Modern video retrieval systems are expected to handle diverse tasks ranging from corpus-level retrieval and fine-grained moment localization to flexible multimodal querying. Specialized architectures achieve strong retrieval performance by training modality-specific encod... | https://arxiv.org/abs/2601.12193 | Academic Papers | svg |
9ee3b806a07fca7e5df441c5f193054f4ada3bad246721020f222319192972d7 | 2026-01-21T00:00:00-05:00 | Coherent Comparison as Information Cost: A Cost-First Ledger Framework for Discrete Dynamics | arXiv:2601.12194v1 Announce Type: new Abstract: We develop an information-theoretic framework for discrete dynamics grounded in a comparison-cost functional on ratios. Given two quantities compared via their ratio \(x=a/b\), we assign a cost \(F(x)\) measuring deviation from equilibrium (\(x=1\)). Requiring coherent co... | https://arxiv.org/abs/2601.12194 | Academic Papers | svg |
c00fb859d044b68ada873b148f6998eff38351194060869175163320160d2d87 | 2026-01-21T00:00:00-05:00 | Understanding Partial Reachability in the Internet Core | arXiv:2601.12196v1 Announce Type: new Abstract: Routing strives to connect all the Internet, but compete: political pressure threatens routing fragmentation; architectural changes such as private clouds, carrier-grade NAT, and firewalls make connectivity conditional; and commercial disputes create partial reachability ... | https://arxiv.org/abs/2601.12196 | Academic Papers | svg |
fd98ea25225ec974ee049e97f528bb4d937a0c198cd9cf4e9f15fec6a94278e3 | 2026-01-21T00:00:00-05:00 | CTC-DID: CTC-Based Arabic dialect identification for streaming applications | arXiv:2601.12199v1 Announce Type: new Abstract: This paper proposes a Dialect Identification (DID) approach inspired by the Connectionist Temporal Classification (CTC) loss function as used in Automatic Speech Recognition (ASR). CTC-DID frames the dialect identification task as a limited-vocabulary ASR system, where di... | https://arxiv.org/abs/2601.12199 | Academic Papers | svg |
ae7bee5e48248879ea3053824da951d0549fca4e017a6899b92796a842e2691b | 2026-01-21T00:00:00-05:00 | Computing Maximal Repeating Subsequences in a String | arXiv:2601.12200v1 Announce Type: new Abstract: In this paper we initiate the study of computing a maximal (not necessarily maximum) repeating pattern in a single input string, where the corresponding problems have been studied (e.g., a maximal common subsequence) only in two or more input strings by Hirota and Sakai s... | https://arxiv.org/abs/2601.12200 | Academic Papers | svg |
aed7f4d3b2a02261b0cd236350724a2862770749ec457630c76b49eec98336ab | 2026-01-21T00:00:00-05:00 | Embryonic Exposure to VPA Influences Chick Vocalisations: A Computational Study | arXiv:2601.12203v1 Announce Type: new Abstract: In young animals like poultry chicks (Gallus gallus), vocalisations convey information about affective and behavioural states. Traditional approaches to vocalisation analysis, relying on manual annotation and predefined categories, introduce biases, limit scalability, and... | https://arxiv.org/abs/2601.12203 | Academic Papers | svg |
d7d06e9d5af6ebaefbfec42726494e0d562c7b9c95c7e4ac1576a8b9487e0216 | 2026-01-21T00:00:00-05:00 | Do Neural Codecs Generalize? A Controlled Study Across Unseen Languages and Non-Speech Tasks | arXiv:2601.12205v1 Announce Type: new Abstract: This paper investigates three crucial yet underexplored aspects of the generalization capabilities of neural audio codecs (NACs): (i) whether NACs can generalize to unseen languages during pre-training, (ii) whether speech-only pre-trained NACs can effectively generalize ... | https://arxiv.org/abs/2601.12205 | Academic Papers | svg |
27147cd5f8ee17265eb4a0ba09fb3ff0fb89ebd69290d4f166480559dc72708d | 2026-01-21T00:00:00-05:00 | CoReflect: Conversational Evaluation via Co-Evolutionary Simulation and Reflective Rubric Refinement | arXiv:2601.12208v1 Announce Type: new Abstract: Evaluating conversational systems in multi-turn settings remains a fundamental challenge. Conventional pipelines typically rely on manually defined rubrics and fixed conversational context$-$a static approach that limits coverage and fails to capture the diverse, emergent... | https://arxiv.org/abs/2601.12208 | Academic Papers | svg |
c0001da266176612ff4d195e6c6750be7c45113d7e115e797829e2991955a558 | 2026-01-21T00:00:00-05:00 | DaggerFFT: A Distributed FFT Framework Using Task Scheduling in Julia | arXiv:2601.12209v1 Announce Type: new Abstract: The Fast Fourier Transform (FFT) is a fundamental numerical technique with widespread application in a range of scientific problems. As scientific simulations attempt to exploit exascale systems, there has been a growing demand for distributed FFT algorithms that can effe... | https://arxiv.org/abs/2601.12209 | Academic Papers | svg |
4386ce11ff49a2ef1bfb69a6eabac8a6b1cbe3f5f89a716b6a1030c80ed0536f | 2026-01-21T00:00:00-05:00 | Solvability of The Output Corridor Control Problem by Pulse-Modulated Feedback | arXiv:2601.12210v1 Announce Type: new Abstract: The problem of maintaining the output of a positive time-invariant single-input single-output system within a predefined corridor of values is treated. For third-order plants possessing a certain structure, it is proven that the problem is always solvable under stationary... | https://arxiv.org/abs/2601.12210 | Academic Papers | svg |
5d7ca72a5364c9d8d859e14828e912074de8abd6021d430d4b410b5cb0646d5f | 2026-01-21T00:00:00-05:00 | Speculative Sampling with Reinforcement Learning | arXiv:2601.12212v1 Announce Type: new Abstract: Inference time latency has remained an open challenge for real world applications of large language models (LLMs). State-of-the-art (SOTA) speculative sampling (SpS) methods for LLMs, like EAGLE-3, use tree-based drafting to explore multiple candidate continuations in par... | https://arxiv.org/abs/2601.12212 | Academic Papers | svg |
7dc1a78e653bbaa088b209533164eede62187d9d4c9018491355f117ab9b8fba | 2026-01-21T00:00:00-05:00 | One-Sided Matrix Completion from Ultra-Sparse Samples | arXiv:2601.12213v1 Announce Type: new Abstract: Matrix completion is a classical problem that has received recurring interest across a wide range of fields. In this paper, we revisit this problem in an ultra-sparse sampling regime, where each entry of an unknown, $n\times d$ matrix $M$ (with $n \ge d$) is observed inde... | https://arxiv.org/abs/2601.12213 | Academic Papers | svg |
15631046b94c1c7db8135baf146064c6420f031dcdef56315dca5a37f0d67075 | 2026-01-21T00:00:00-05:00 | Wavelet-Driven Masked Multiscale Reconstruction for PPG Foundation Models | arXiv:2601.12215v1 Announce Type: new Abstract: Wearable foundation models have the potential to transform digital health by learning transferable representations from large-scale biosignals collected in everyday settings. While recent progress has been made in large-scale pretraining, most approaches overlook the spec... | https://arxiv.org/abs/2601.12215 | Academic Papers | svg |
6f7af8d38198f027e7551df327f339bfe3afda8652038d9814424e0fe9a00e2b | 2026-01-21T00:00:00-05:00 | Canonicalization of Batched Einstein Summations for Tuning Retrieval | arXiv:2601.12220v1 Announce Type: new Abstract: We present an algorithm for normalizing \emph{Batched Einstein Summation} expressions by mapping mathematically equivalent formulations to a unique normal form. Batches of einsums with the same Einstein notation that exhibit substantial data reuse appear frequently in fin... | https://arxiv.org/abs/2601.12220 | Academic Papers | svg |
a7a9b68a171826a8c00265d2c05a11a36cdd9b2a242c717d1bf5d8085ccfb215 | 2026-01-21T00:00:00-05:00 | Song Aesthetics Evaluation with Multi-Stem Attention and Hierarchical Uncertainty Modeling | arXiv:2601.12222v1 Announce Type: new Abstract: Music generative artificial intelligence (AI) is rapidly expanding music content, necessitating automated song aesthetics evaluation. However, existing studies largely focus on speech, audio or singing quality, leaving song aesthetics underexplored. Moreover, conventional... | https://arxiv.org/abs/2601.12222 | Academic Papers | svg |
7d9819fe436e08243ba3f0769422402a9e7487e9e5f2d9c10a634f5140e5f233 | 2026-01-21T00:00:00-05:00 | Where It Moves, It Matters: Referring Surgical Instrument Segmentation via Motion | arXiv:2601.12224v1 Announce Type: new Abstract: Enabling intuitive, language-driven interaction with surgical scenes is a critical step toward intelligent operating rooms and autonomous surgical robotic assistance. However, the task of referring segmentation, localizing surgical instruments based on natural language de... | https://arxiv.org/abs/2601.12224 | Academic Papers | svg |
c28f308373acc9d9056cf720b64d0f8c9e164f6efac1a07db0e2ccc2b737229d | 2026-01-21T00:00:00-05:00 | Learning Longitudinal Health Representations from EHR and Wearable Data | arXiv:2601.12227v1 Announce Type: new Abstract: Foundation models trained on electronic health records show strong performance on many clinical prediction tasks but are limited by sparse and irregular documentation. Wearable devices provide dense continuous physiological signals but lack semantic grounding. Existing me... | https://arxiv.org/abs/2601.12227 | Academic Papers | svg |
fe1f0d612a7146e43bbd7cae68174965dcaffc1b08f27644e7376fc3d2ff12c1 | 2026-01-21T00:00:00-05:00 | Classical-Quantum Channel Resolvability Using Matrix Multiplicative Weight Update Algorithm | arXiv:2601.12230v1 Announce Type: new Abstract: We study classical-quantum (C-Q) channel resolvability. C-Q channel resolvability has been proved by only random coding in the literature. In our previous study, we proved channel resolvability by deterministic coding, using multiplicative weight update algorithm. We exte... | https://arxiv.org/abs/2601.12230 | Academic Papers | svg |
62c60e42cd0a193723a9ad6871152672fcbedbfeca1cf7ebbeedaba294095c8d | 2026-01-21T00:00:00-05:00 | Wavelet-Aware Anomaly Detection in Multi-Channel User Logs via Deviation Modulation and Resolution-Adaptive Attention | arXiv:2601.12231v1 Announce Type: new Abstract: Insider threat detection is a key challenge in enterprise security, relying on user activity logs that capture rich and complex behavioral patterns. These logs are often multi-channel, non-stationary, and anomalies are rare, making anomaly detection challenging. To addres... | https://arxiv.org/abs/2601.12231 | Academic Papers | svg |
a0ebfff3ccb151606d7326a9b56b21e377d2fddc8f753e553b19d044d399c1d8 | 2026-01-21T00:00:00-05:00 | DiffusionQC: Artifact Detection in Histopathology via Diffusion Model | arXiv:2601.12233v1 Announce Type: new Abstract: Digital pathology plays a vital role across modern medicine, offering critical insights for disease diagnosis, prognosis, and treatment. However, histopathology images often contain artifacts introduced during slide preparation and digitization. Detecting and excluding th... | https://arxiv.org/abs/2601.12233 | Academic Papers | svg |
be3232b9708b15004b6f4067594bd50b6cfcd10efdd24e624ca5baa0ca5c6869 | 2026-01-21T00:00:00-05:00 | Proc3D: Procedural 3D Generation and Parametric Editing of 3D Shapes with Large Language Models | arXiv:2601.12234v1 Announce Type: new Abstract: Generating 3D models has traditionally been a complex task requiring specialized expertise. While recent advances in generative AI have sought to automate this process, existing methods produce non-editable representation, such as meshes or point clouds, limiting their ad... | https://arxiv.org/abs/2601.12234 | Academic Papers | svg |
9fc2b5b634f0d9e14496ed8284f612fd571dffc52b8afd515e7e0ea5f7b42769 | 2026-01-21T00:00:00-05:00 | Analyzing the Impact of EV Battery Charging on the Distribution Network | arXiv:2601.12236v1 Announce Type: new Abstract: Many countries are rapidly adopting electric vehicles (EVs) due to their meager running cost and environment-friendly nature. EVs are likely to dominate the internal combustion (IC) engine cars entirely over the next few years. With the rise in popularity of EVs, adverse ... | https://arxiv.org/abs/2601.12236 | Academic Papers | svg |
db662957f60180dee6c9c7156aa8e6063058246dbdd14245e0b0a518da4c3c8f | 2026-01-21T00:00:00-05:00 | Power Aware Dynamic Reallocation For Inference | arXiv:2601.12241v1 Announce Type: new Abstract: Disaggregation has emerged as a powerful strategy for optimizing large language model (LLM) inference by separating compute-intensive prefill and memory-bound decode phases across specialized GPUs. This separation improves utilization and throughput under fixed hardware c... | https://arxiv.org/abs/2601.12241 | Academic Papers | svg |
a6d6e5f3313588b16288506a16f714bf63d680d8498522fdadf6ab60f3f58d22 | 2026-01-21T00:00:00-05:00 | Optimal Power Allocation and Sub-Optimal Channel Assignment for Downlink NOMA Systems Using Deep Reinforcement Learning | arXiv:2601.12242v1 Announce Type: new Abstract: In recent years, Non-Orthogonal Multiple Access (NOMA) system has emerged as a promising candidate for multiple access frameworks due to the evolution of deep machine learning, trying to incorporate deep machine learning into the NOMA system. The main motivation for such ... | https://arxiv.org/abs/2601.12242 | Academic Papers | svg |
a0ec56b5752c7ab1fb9e48192c4666bb9d1a11f778fef10ac7f756f64836f069 | 2026-01-21T00:00:00-05:00 | Less is More: Label-Guided Summarization of Procedural and Instructional Videos | arXiv:2601.12243v1 Announce Type: new Abstract: Video summarization helps turn long videos into clear, concise representations that are easier to review, document, and analyze, especially in high-stakes domains like surgical training. Prior work has progressed from using basic visual features like color, motion, and st... | https://arxiv.org/abs/2601.12243 | Academic Papers | svg |
985c525197ca8f89319b4acd8e1873d0b4953f44652db283b2c7a18c605ba34d | 2026-01-21T00:00:00-05:00 | A Comprehensive Review of Bio-Inspired Approaches to Coordination, Communication, and System Architecture in Underwater Swarm Robotics | arXiv:2601.12244v1 Announce Type: new Abstract: The increasing complexity of marine operations has intensified the need for intelligent robotic systems to support ocean observation, exploration, and resource management. Underwater swarm robotics offers a promising framework that extends the capabilities of individual a... | https://arxiv.org/abs/2601.12244 | Academic Papers | svg |
f4a8ef5d86aa941e6709cb74a723c971f7df64ad32edaa650c30ba907b822fb7 | 2026-01-21T00:00:00-05:00 | Sound2Hap: Learning Audio-to-Vibrotactile Haptic Generation from Human Ratings | arXiv:2601.12245v1 Announce Type: new Abstract: Environmental sounds like footsteps, keyboard typing, or dog barking carry rich information and emotional context, making them valuable for designing haptics in user applications. Existing audio-to-vibration methods, however, rely on signal-processing rules tuned for musi... | https://arxiv.org/abs/2601.12245 | Academic Papers | svg |
3e0892457d580be9b50caf20fa4aa3fc4402ff5aca0a29c35f87c19654f0fda8 | 2026-01-21T00:00:00-05:00 | Explicit symmetric low-regularity integrators for the semilinear Klein-Gordon equation | arXiv:2601.12246v1 Announce Type: new Abstract: This paper is concerned with the design and analysis of symmetric low-regularity integrators for the semilinear Klein-Gordon equation. We first propose a general symmetrization procedure that allows for the systematic construction of symmetric schemes from existing explic... | https://arxiv.org/abs/2601.12246 | Academic Papers | svg |
3d3601de15446cc5dc93175b074d08a2c5e248295892cb98bf1aea3f7551d7d3 | 2026-01-21T00:00:00-05:00 | Plan, Verify and Fill: A Structured Parallel Decoding Approach for Diffusion Language Models | arXiv:2601.12247v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) present a promising non-sequential paradigm for text generation, distinct from standard autoregressive (AR) approaches. However, current decoding strategies often adopt a reactive stance, underutilizing the global bidirectional context to ... | https://arxiv.org/abs/2601.12247 | Academic Papers | svg |
0d9b1bc72260fac4673119491dba9ec93d810327648b05f15ebc6bb297d8a992 | 2026-01-21T00:00:00-05:00 | An Innovative Framework for Breast Cancer Detection Using Pyramid Adaptive Atrous Convolution, Transformer Integration, and Multi-Scale Feature Fusion | arXiv:2601.12249v1 Announce Type: new Abstract: Breast cancer is one of the most common cancers among women worldwide, and its accurate and timely diagnosis plays a critical role in improving treatment outcomes. This thesis presents an innovative framework for detecting malignant masses in mammographic images by integr... | https://arxiv.org/abs/2601.12249 | Academic Papers | svg |
5ec53cb64091923f4beeed069b086e7926910d2121fe10b0d98109068ee2821a | 2026-01-21T00:00:00-05:00 | Breaking Coordinate Overfitting: Geometry-Aware WiFi Sensing for Cross-Layout 3D Pose Estimation | arXiv:2601.12252v1 Announce Type: new Abstract: WiFi-based 3D human pose estimation offers a low-cost and privacy-preserving alternative to vision-based systems for smart interaction. However, existing approaches rely on visual 3D poses as supervision and directly regress CSI to a camera-based coordinate system. We fin... | https://arxiv.org/abs/2601.12252 | Academic Papers | svg |
5c27168477f26e2a9f58a158884dfc0dc4443c2be8405d45d15147153d054f60 | 2026-01-21T00:00:00-05:00 | Federated Joint Learning for Domain and Class Generalization | arXiv:2601.12253v1 Announce Type: new Abstract: Efficient fine-tuning of visual-language models like CLIP has become crucial due to their large-scale parameter size and extensive pretraining requirements. Existing methods typically address either the issue of unseen classes or unseen domains in isolation, without consi... | https://arxiv.org/abs/2601.12253 | Academic Papers | svg |
1967c8f7c4dea3f89bbb9daf122343fa3bb50318d2bd975fa02c7ad54b8866c3 | 2026-01-21T00:00:00-05:00 | Confidence-based Filtering for Speech Dataset Curation with Generative Speech Enhancement Using Discrete Tokens | arXiv:2601.12254v1 Announce Type: new Abstract: Generative speech enhancement (GSE) models show great promise in producing high-quality clean speech from noisy inputs, enabling applications such as curating noisy text-to-speech (TTS) datasets into high-quality ones. However, GSE models are prone to hallucination errors... | https://arxiv.org/abs/2601.12254 | Academic Papers | svg |
32458ac5daf09645d1104fcc68582d8e6c9eaefcea23089cedcf57ae3e8711a6 | 2026-01-21T00:00:00-05:00 | Improving Large Molecular Language Model via Relation-aware Multimodal Collaboration | arXiv:2601.12256v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated their instruction-following capabilities and achieved powerful performance on various tasks. Inspired by their success, recent works in the molecular domain have led to the development of large molecular language models (LMLM... | https://arxiv.org/abs/2601.12256 | Academic Papers | svg |
a1f4ee0a444acf11ccf0f1100b019f534a3b8515713f28f4d8b9c98e0869f7fc | 2026-01-21T00:00:00-05:00 | Soft Shadow Diffusion (SSD): Physics-inspired Learning for 3D Computational Periscopy | arXiv:2601.12257v1 Announce Type: new Abstract: Conventional imaging requires a line of sight to create accurate visual representations of a scene. In certain circumstances, however, obtaining a suitable line of sight may be impractical, dangerous, or even impossible. Non-line-of-sight (NLOS) imaging addresses this cha... | https://arxiv.org/abs/2601.12257 | Academic Papers | svg |
90dc66a37c4f244240960d1ed395145dc8ea5b0761015b262fb1dcabd6434aa4 | 2026-01-21T00:00:00-05:00 | FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains | arXiv:2601.12259v1 Announce Type: new Abstract: Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, FutureX-PublicHealth, FutureX-NaturalDisaster, and FutureX-Search. These together form a special... | https://arxiv.org/abs/2601.12259 | Academic Papers | svg |
6815f3ef2292448ba5caaa8747eba860d95f83db3a7296b4186f2c5491f44022 | 2026-01-21T00:00:00-05:00 | Docs2Synth: A Synthetic Data Trained Retriever Framework for Scanned Visually Rich Documents Understanding | arXiv:2601.12260v1 Announce Type: new Abstract: Document understanding (VRDU) in regulated domains is particularly challenging, since scanned documents often contain sensitive, evolving, and domain specific knowledge. This leads to two major challenges: the lack of manual annotations for model adaptation and the diffic... | https://arxiv.org/abs/2601.12260 | Academic Papers | svg |
05a80d107cd7f3e431f501c58770e45efafd57f043cb82ea55cbc8b01d236a60 | 2026-01-21T00:00:00-05:00 | Environment-Aware Code Generation: How far are We? | arXiv:2601.12262v1 Announce Type: new Abstract: Recent progress in large language models (LLMs) has improved code generation, but most evaluations still test isolated, small-scale code (e.g., a single function) under default or unspecified software environments. As a result, it is unclear whether LLMs can reliably gene... | https://arxiv.org/abs/2601.12262 | Academic Papers | svg |
563ff8b9c7695d1e5d41cf0204e4b6aa806e1cefeb7a48cce85f1b5bfcb89e77 | 2026-01-21T00:00:00-05:00 | Multimodal Generative Engine Optimization: Rank Manipulation for Vision-Language Model Rankers | arXiv:2601.12263v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are rapidly replacing unimodal encoders in modern retrieval and recommendation systems. While their capabilities are well-documented, their robustness against adversarial manipulation in competitive ranking scenarios remains largely unexplore... | https://arxiv.org/abs/2601.12263 | Academic Papers | svg |
3f78a156a485aafcf8f61d6413ec4fd7c2ef11978f20d7cd7c9f5b32f57af0a7 | 2026-01-21T00:00:00-05:00 | Statistical Firefly Algorithm for Truss Topology Optimization | arXiv:2601.12265v1 Announce Type: new Abstract: This study proposes an algorithm titled a statistical firefly algorithm (SFA) for truss topology optimization. In the proposed algorithm, historical results of fireflies' motions are used in hypothesis testing to limit the motions of fireflies that are suggested by curren... | https://arxiv.org/abs/2601.12265 | Academic Papers | svg |
dec94b61b451a670cf1c473739c7c1b53ac377cde9de5f1ad8dc3227a094f86a | 2026-01-21T00:00:00-05:00 | Opportunistic Scheduling for Optimal Spot Instance Savings in the Cloud | arXiv:2601.12266v1 Announce Type: new Abstract: We study the problem of scheduling delay-sensitive jobs over spot and on-demand cloud instances to minimize average cost while meeting an average delay constraint. Jobs arrive as a general stochastic process, and incur different costs based on the instance type. This work... | https://arxiv.org/abs/2601.12266 | Academic Papers | svg |
eb6ff1c47d393c652f8c3978e2b37734e08692c22b66286a6ba26ea7d865d6c4 | 2026-01-21T00:00:00-05:00 | Simulated Annealing Enhances Theory-of-Mind Reasoning in Autoregressive Language Models | arXiv:2601.12269v1 Announce Type: new Abstract: Autoregressive language models are next-token predictors and have been criticized for only optimizing surface plausibility (i.e., local coherence) rather than maintaining correct latent-state representations (i.e., global coherence). Because Theory of Mind (ToM) tasks cru... | https://arxiv.org/abs/2601.12269 | Academic Papers | svg |
c3b3f989ba86ee631f31915713bde5828ee9c94bd897c42c36f8eb65497cf602 | 2026-01-21T00:00:00-05:00 | SplittingSecrets: A Compiler-Based Defense for Preventing Data Memory-Dependent Prefetcher Side-Channels | arXiv:2601.12270v1 Announce Type: new Abstract: Traditional side-channels take advantage of secrets being used as inputs to unsafe instructions, used for memory accesses, or used in control flow decisions. Constant-time programming, which restricts such code patterns, has been widely adopted as a defense against these ... | https://arxiv.org/abs/2601.12270 | Academic Papers | svg |
510249bc3b93ed7039225597f4376580e1dda512d56b511db8f07bc76f2805f5 | 2026-01-21T00:00:00-05:00 | AgenticPruner: MAC-Constrained Neural Network Compression via LLM-Driven Strategy Search | arXiv:2601.12272v1 Announce Type: new Abstract: Neural network pruning remains essential for deploying deep learning models on resource-constrained devices, yet existing approaches primarily target parameter reduction without directly controlling computational cost. This yields unpredictable inference latency in deploy... | https://arxiv.org/abs/2601.12272 | Academic Papers | svg |
7bc4812a6c706c1a1858925e47952f65e4ae6429c769c972c782b451893d6003 | 2026-01-21T00:00:00-05:00 | Leveraging Mutation Analysis for LLM-based Repair of Quantum Programs | arXiv:2601.12273v1 Announce Type: new Abstract: In recent years, Automated Program Repair (APR) techniques specifically designed for quantum programs have been proposed. However, existing approaches often suffer from low repair success rates or poor understandability of the generated patches. In this study, we construc... | https://arxiv.org/abs/2601.12273 | Academic Papers | svg |
2982009f8c075671762d3e587c9076b8513218b0b7df37e8ff0640945dda5c04 | 2026-01-21T00:00:00-05:00 | Hybrid Concolic Testing with Large Language Models for Guided Path Exploration | arXiv:2601.12274v1 Announce Type: new Abstract: Concolic testing, a powerful hybrid software testing technique, has historically been plagued by fundamental limitations such as path explosion and the high cost of constraint solving, which hinder its practical application in large-scale, real-world software systems. Thi... | https://arxiv.org/abs/2601.12274 | Academic Papers | svg |
d514c3b1120306a2c28411e0ade5b5475e00b53a1a26e2ed85ff029d649b80e2 | 2026-01-21T00:00:00-05:00 | Predictive Prototyping: Evaluating Design Concepts with ChatGPT | arXiv:2601.12276v1 Announce Type: new Abstract: The design-build-test cycle is essential for innovation, but physical prototyping is often slow and expensive. Although physics-based simulation and strategic prototyping can reduce cost, meaningful evaluation is frequently constrained until an integrated prototype is bui... | https://arxiv.org/abs/2601.12276 | Academic Papers | svg |
b8f288b7f87b51a87951943b076829669d6a10bc3ddee71a4af238ceb5e0f234 | 2026-01-21T00:00:00-05:00 | An Efficient and Multi-Modal Navigation System with One-Step World Model | arXiv:2601.12277v1 Announce Type: new Abstract: Navigation is a fundamental capability for mobile robots. While the current trend is to use learning-based approaches to replace traditional geometry-based methods, existing end-to-end learning-based policies often struggle with 3D spatial reasoning and lack a comprehensi... | https://arxiv.org/abs/2601.12277 | Academic Papers | svg |
0965d336afd49f06decdbaeca723065e617552e1c69b1d500ec158c228acb432 | 2026-01-21T00:00:00-05:00 | HCFT: Hierarchical Convolutional Fusion Transformer for EEG Decoding | arXiv:2601.12279v1 Announce Type: new Abstract: Electroencephalography (EEG) decoding requires models that can effectively extract and integrate complex temporal, spectral, and spatial features from multichannel signals. To address this challenge, we propose a lightweight and generalizable decoding framework named Hier... | https://arxiv.org/abs/2601.12279 | Academic Papers | svg |
33ee5be8bdcdfb276fe452c8fe45168c2fce1b39163d28df2084151320ebfff7 | 2026-01-21T00:00:00-05:00 | Democratizing Music Therapy: LLM-Based Automated EEG Analysis and Progress Tracking for Low-Cost Home Devices | arXiv:2601.12280v1 Announce Type: new Abstract: Home-based music therapy devices require accessible and cost-effective solutions for users to understand and track their therapeutic progress. Traditional physiological signal analysis, particularly EEG interpretation, relies heavily on domain experts, creating barriers t... | https://arxiv.org/abs/2601.12280 | Academic Papers | svg |
e135432833f20e5843fac9cbed113c24559da2e833813b1c197aca1ffb010a79 | 2026-01-21T00:00:00-05:00 | CytoCLIP: Learning Cytoarchitectural Characteristics in Developing Human Brain Using Contrastive Language Image Pre-Training | arXiv:2601.12282v1 Announce Type: new Abstract: The functions of different regions of the human brain are closely linked to their distinct cytoarchitecture, which is defined by the spatial arrangement and morphology of the cells. Identifying brain regions by their cytoarchitecture enables various scientific analyses of... | https://arxiv.org/abs/2601.12282 | Academic Papers | svg |
d1c29979eb1ef325a51474d8684a4387b8c824f43af340424ed6e19ad2163668 | 2026-01-21T00:00:00-05:00 | SDiT: Semantic Region-Adaptive for Diffusion Transformers | arXiv:2601.12283v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve state-of-the-art performance in text-to-image synthesis but remain computationally expensive due to the iterative nature of denoising and the quadratic cost of global attention. In this work, we observe that denoising dynamics are spa... | https://arxiv.org/abs/2601.12283 | Academic Papers | svg |
d0ba8f145b771339854565b53d420af0763220da333b47cc94836532c49dcee9 | 2026-01-21T00:00:00-05:00 | How Safe Is Your Data in Connected and Autonomous Cars: A Consumer Advantage or a Privacy Nightmare ? | arXiv:2601.12284v1 Announce Type: new Abstract: The rapid evolution of the automobile sector, driven by advancements in connected and autonomous vehicles (CAVs), has transformed how vehicles communicate, operate, and interact with their surroundings. Technologies such as Vehicle-to-Everything (V2X) communication enable... | https://arxiv.org/abs/2601.12284 | Academic Papers | svg |
3e10a5f27b99e15100a0867ea264be02912684233f3c855de7c55235bc47141b | 2026-01-21T00:00:00-05:00 | LegacyAvatars: Volumetric Face Avatars For Traditional Graphics Pipelines | arXiv:2601.12285v1 Announce Type: new Abstract: We introduce a novel representation for efficient classical rendering of photorealistic 3D face avatars. Leveraging recent advances in radiance fields anchored to parametric face models, our approach achieves controllable volumetric rendering of complex facial features, i... | https://arxiv.org/abs/2601.12285 | Academic Papers | svg |
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