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ed39c0f08e640397fc1525c49b649c7f4f2bc46040fda4f0140dbabef84a293b | 2026-01-13T00:00:00-05:00 | How to predict creativity ratings from written narratives: A comparison of co-occurrence and textual forma mentis networks | arXiv:2601.07327v1 Announce Type: new Abstract: This tutorial paper provides a step-by-step workflow for building and analysing semantic networks from short creative texts. We introduce and compare two widely used text-to-network approaches: word co-occurrence networks and textual forma mentis networks (TFMNs). We also... | https://arxiv.org/abs/2601.07327 | Academic Papers | svg |
23f946fdf85e4288cdbdd85708838778b9dcd7eec62872f46b846e2af6a13dbd | 2026-01-13T00:00:00-05:00 | BayesRAG: Probabilistic Mutual Evidence Corroboration for Multimodal Retrieval-Augmented Generation | arXiv:2601.07329v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become a pivotal paradigm for Large Language Models (LLMs), yet current approaches struggle with visually rich documents by treating text and images as isolated retrieval targets. Existing methods relying solely on cosine similarit... | https://arxiv.org/abs/2601.07329 | Academic Papers | svg |
082d5eceddb7562c490b1709ea596f8d20c6ddc8c9a608e231360c5c40b47bfe | 2026-01-13T00:00:00-05:00 | SEE: Signal Embedding Energy for Quantifying Noise Interference in Large Audio Language Models | arXiv:2601.07331v1 Announce Type: new Abstract: Large Audio Language Models (LALMs) have been widely applied in real-time scenarios, such as in-car assistants and online meeting comprehension. In practice, audio inputs are often corrupted by device and environmental noise, leading to performance degradation. However, e... | https://arxiv.org/abs/2601.07331 | Academic Papers | svg |
0bbcf84b6f7aacf77941e28e7075922f4a3f47ddf9f02084a6136d794940aa49 | 2026-01-13T00:00:00-05:00 | OSCAR: Open-Set CAD Retrieval from a Language Prompt and a Single Image | arXiv:2601.07333v1 Announce Type: new Abstract: 6D object pose estimation plays a crucial role in scene understanding for applications such as robotics and augmented reality. To support the needs of ever-changing object sets in such context, modern zero-shot object pose estimators were developed to not require object-s... | https://arxiv.org/abs/2601.07333 | Academic Papers | svg |
3881caeaa4ef0c03363c5a82fad66e1ed957e5e2dc561feb419bd3ed53a19762 | 2026-01-13T00:00:00-05:00 | Examining the Effectiveness of Transformer-Based Smart Contract Vulnerability Scan | arXiv:2601.07334v1 Announce Type: new Abstract: Smart contract technology facilitates self-executing agreements on the blockchain, eliminating dependency on an external trusted authority. However, smart contracts may expose vulnerabilities that can lead to financial losses and disruptions in decentralized applications.... | https://arxiv.org/abs/2601.07334 | Academic Papers | svg |
371910a2dac7d43fdd864b5f79958a6d45a0441d3b5e2da47c3c25c7e1f34490 | 2026-01-13T00:00:00-05:00 | Reconstruction Guided Few-shot Network For Remote Sensing Image Classification | arXiv:2601.07335v1 Announce Type: new Abstract: Few-shot remote sensing image classification is challenging due to limited labeled samples and high variability in land-cover types. We propose a reconstruction-guided few-shot network (RGFS-Net) that enhances generalization to unseen classes while preserving consistency ... | https://arxiv.org/abs/2601.07335 | Academic Papers | svg |
338c8a6667e77f237c58e3e2990c527f0f5cead4b650be621b97968ba6eed28a | 2026-01-13T00:00:00-05:00 | Improved lower bounds for the maximum size of Condorcet domains | arXiv:2601.07336v1 Announce Type: new Abstract: Condorcet domains are sets of linear orders with the property that, whenever voters' preferences are restricted to the domain, the pairwise majority relation (for an odd number of voters) is transitive and hence a linear order. Determining the maximum size of a Condorcet ... | https://arxiv.org/abs/2601.07336 | Academic Papers | svg |
903ce107c1a294164973c2afd1e6ead66af62c933cd47a0b927f98f972885085 | 2026-01-13T00:00:00-05:00 | Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation | arXiv:2601.07338v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly advanced Machine Translation (MT), applying them to linguistically complex domains-such as Social Network Services, literature etc. In these scenarios, translations often require handling non-literal expressions, leading to ... | https://arxiv.org/abs/2601.07338 | Academic Papers | svg |
04c0505ffb5432e8a40792195fd606eea5e51b3b0cae5238f64614db541948eb | 2026-01-13T00:00:00-05:00 | On the Extremal Source Key Rates for Secure Storage over Graphs | arXiv:2601.07340v1 Announce Type: new Abstract: This paper investigates secure storage codes over graphs, where multiple independent source symbols are encoded and stored at graph nodes subject to edge-wise correctness and security constraints. For each edge, a specified subset of source symbols must be recoverable fro... | https://arxiv.org/abs/2601.07340 | Academic Papers | svg |
3a15badfe5d34694b38222e6ebb8f1494c673978f5c1cf56391e8097840aa25b | 2026-01-13T00:00:00-05:00 | Agentic Diagnostic Reasoning over Telecom and Datacenter Infrastructure | arXiv:2601.07342v1 Announce Type: new Abstract: Large-scale telecom and datacenter infrastructures rely on multi-layered service and resource models, where failures propagate across physical and logical components and affect multiple customers. Traditional approaches to root cause analysis(RCA) rely on hard-coded graph... | https://arxiv.org/abs/2601.07342 | Academic Papers | svg |
20691a6669e97fb6027204a451d388751d81ae545b71e215094ce54664233376 | 2026-01-13T00:00:00-05:00 | PulseMind: A Multi-Modal Medical Model for Real-World Clinical Diagnosis | arXiv:2601.07344v1 Announce Type: new Abstract: Recent advances in medical multi-modal models focus on specialized image analysis like dermatology, pathology, or radiology. However, they do not fully capture the complexity of real-world clinical diagnostics, which involve heterogeneous inputs and require ongoing contex... | https://arxiv.org/abs/2601.07344 | Academic Papers | svg |
589f912970fe5f099a55ce74e2acab4a42b2c0ec0ba7f850c85464db34d54dc0 | 2026-01-13T00:00:00-05:00 | DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models | arXiv:2601.07347v1 Announce Type: new Abstract: The "reversal curse" refers to the phenomenon where large language models (LLMs) exhibit predominantly unidirectional behavior when processing logically bidirectional relationships. Prior work attributed this to autoregressive training -- predicting the next token inheren... | https://arxiv.org/abs/2601.07347 | Academic Papers | svg |
9dfa6efdf914470b9f1d9b44aa927141a7a69f1b3d8d6a7f3e4b0cfd8a743932 | 2026-01-13T00:00:00-05:00 | Controlled Self-Evolution for Algorithmic Code Optimization | arXiv:2601.07348v1 Announce Type: new Abstract: Self-evolution methods enhance code generation through iterative "generate-verify-refine" cycles, yet existing approaches suffer from low exploration efficiency, failing to discover solutions with superior complexity within limited budgets. This inefficiency stems from in... | https://arxiv.org/abs/2601.07348 | Academic Papers | svg |
b3385e6b08d0acda51bb6faf4d35979863dcb2b00f76e5066388a2dff37e1cd6 | 2026-01-13T00:00:00-05:00 | Reward Modeling from Natural Language Human Feedback | arXiv:2601.07349v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable reward (RLVR) on preference data has become the mainstream approach for training Generative Reward Models (GRMs). Typically in pairwise rewarding tasks, GRMs generate reasoning chains ending with critiques and preference labels, and ... | https://arxiv.org/abs/2601.07349 | Academic Papers | svg |
a2e382c0711753bd67cc658e91b07046f0c4c563b5c80cafa9fa6b26dcc795cd | 2026-01-13T00:00:00-05:00 | Beyond Hard Masks: Progressive Token Evolution for Diffusion Language Models | arXiv:2601.07351v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) offer a promising alternative for language modeling by enabling parallel decoding through iterative refinement. However, most DLMs rely on hard binary masking and discrete token assignments, which hinder the revision of early decisions and... | https://arxiv.org/abs/2601.07351 | Academic Papers | svg |
9a5774bb598746354470124c68e17c6c97d8364a6c03cd018b17b3ccbccfbd34 | 2026-01-13T00:00:00-05:00 | TALON: Confidence-Aware Speculative Decoding with Adaptive Token Trees | arXiv:2601.07353v1 Announce Type: new Abstract: Speculative decoding (SD) has become a standard technique for accelerating LLM inference without sacrificing output quality. Recent advances in speculative decoding have shifted from sequential chain-based drafting to tree-structured generation, where the draft model cons... | https://arxiv.org/abs/2601.07353 | Academic Papers | svg |
618bd800178819d7fa4df40f9b34e521ff9240fa2e698e887defdb6d13856e7d | 2026-01-13T00:00:00-05:00 | Semantic Compression of LLM Instructions via Symbolic Metalanguages | arXiv:2601.07354v1 Announce Type: new Abstract: We introduce MetaGlyph, a symbolic language for compressing prompts by encoding instructions as mathematical symbols rather than prose. Unlike systems requiring explicit decoding rules, MetaGlyph uses symbols like $\in$ (membership) and $\Rightarrow$ (implication) that mo... | https://arxiv.org/abs/2601.07354 | Academic Papers | svg |
99b0ecf6106e19599492f7205c4e0d6c3413181decb7570ebfab6872a599d396 | 2026-01-13T00:00:00-05:00 | Fast and Provable Nonconvex Robust Matrix Completion | arXiv:2601.07355v1 Announce Type: new Abstract: This paper studies the robust matrix completion problem and a computationally efficient non-convex method called ARMC has been proposed. This method is developed by introducing subspace projection to a singular value thresholding based method when updating the low rank pa... | https://arxiv.org/abs/2601.07355 | Academic Papers | svg |
e1e025bd88fd893260f878141a79638ff6c92791e2ecc897f1cd4d73dfc6cff2 | 2026-01-13T00:00:00-05:00 | Seeing Right but Saying Wrong: Inter- and Intra-Layer Refinement in MLLMs without Training | arXiv:2601.07359v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong capabilities across a variety of vision-language tasks. However, their internal reasoning often exhibits a critical inconsistency: although deeper layers may attend to the correct visual regions, final pred... | https://arxiv.org/abs/2601.07359 | Academic Papers | svg |
e45b3a9fac7dbd8cd3c72f676d90d3f206dfeba581081e81279ebcd00de9f8a6 | 2026-01-13T00:00:00-05:00 | Large-Scale Autonomous Gas Monitoring for Volcanic Environments: A Legged Robot on Mount Etna | arXiv:2601.07362v1 Announce Type: new Abstract: Volcanic gas emissions are key precursors of eruptive activity. Yet, obtaining accurate near-surface measurements remains hazardous and logistically challenging, motivating the need for autonomous solutions. Limited mobility in rough volcanic terrain has prevented wheeled... | https://arxiv.org/abs/2601.07362 | Academic Papers | svg |
2c1fc4918c6c923e3ed484c600f0d5db49ed225351a19ef9c4c55f5394227478 | 2026-01-13T00:00:00-05:00 | On the universal definition of intelligence | arXiv:2601.07364v1 Announce Type: new Abstract: This paper aims to propose a universal definition of intelligence that enables fair and consistent comparison of human and artificial intelligence (AI). With the rapid development of AI technology in recent years, how to compare and evaluate human and AI intelligence has ... | https://arxiv.org/abs/2601.07364 | Academic Papers | svg |
76e3e22b4d91c279cfec947453c527fcc1f2005d11607a28c1f9af15f85d8003 | 2026-01-13T00:00:00-05:00 | HiVid-Narrator: Hierarchical Video Narrative Generation with Scene-Primed ASR-anchored Compression | arXiv:2601.07366v1 Announce Type: new Abstract: Generating structured narrations for real-world e-commerce videos requires models to perceive fine-grained visual details and organize them into coherent, high-level stories--capabilities that existing approaches struggle to unify. We introduce the E-commerce Hierarchical... | https://arxiv.org/abs/2601.07366 | Academic Papers | svg |
c3c46a1e03ad71c31cb7504c800576b78e131bece87319776e5f5e2f7d12b7c3 | 2026-01-13T00:00:00-05:00 | FOCAL: A Novel Benchmarking Technique for Multi-modal Agents | arXiv:2601.07367v1 Announce Type: new Abstract: With the recent advancements in reasoning capa- bilities, tool calling using MCP servers and Audio Language Models (ALMs), development and integration of multi-modal agents (with voice and text support) has come to the industry forefront. Cascading pipelines for voice age... | https://arxiv.org/abs/2601.07367 | Academic Papers | svg |
9abfd1a5b8a54f5e4f6eb4bcbf7c07bb88c70ef6f8e5effb49d500d8ab985ce1 | 2026-01-13T00:00:00-05:00 | Interpretable Text Classification Applied to the Detection of LLM-generated Creative Writing | arXiv:2601.07368v1 Announce Type: new Abstract: We consider the problem of distinguishing human-written creative fiction (excerpts from novels) from similar text generated by an LLM. Our results show that, while human observers perform poorly (near chance levels) on this binary classification task, a variety of machine... | https://arxiv.org/abs/2601.07368 | Academic Papers | svg |
a08cdb16dc63ec78641431157b5e0888ec349713d4c0d9e5488bfdcfe80718b5 | 2026-01-13T00:00:00-05:00 | Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models | arXiv:2601.07372v1 Announce Type: new Abstract: While Mixture-of-Experts (MoE) scales capacity via conditional computation, Transformers lack a native primitive for knowledge lookup, forcing them to inefficiently simulate retrieval through computation. To address this, we introduce conditional memory as a complementary... | https://arxiv.org/abs/2601.07372 | Academic Papers | svg |
76c5a2a95bf565e3cff6055cc265b29628e1a039563fc62edc31c8254e777ad2 | 2026-01-13T00:00:00-05:00 | GROKE: Vision-Free Navigation Instruction Evaluation via Graph Reasoning on OpenStreetMap | arXiv:2601.07375v1 Announce Type: new Abstract: The evaluation of navigation instructions remains a persistent challenge in Vision-and-Language Navigation (VLN) research. Traditional reference-based metrics such as BLEU and ROUGE fail to capture the functional utility of spatial directives, specifically whether an inst... | https://arxiv.org/abs/2601.07375 | Academic Papers | svg |
b721ecaf9901d613ed2f8195ec6b7951ec54048d380581e35329a7780da81b2a | 2026-01-13T00:00:00-05:00 | OpenTinker: Separating Concerns in Agentic Reinforcement Learning | arXiv:2601.07376v1 Announce Type: new Abstract: We introduce OpenTinker, an infrastructure for reinforcement learning (RL) of large language model (LLM) agents built around a separation of concerns across algorithm design, execution, and agent-environment interaction. Rather than relying on monolithic, end-to-end RL pi... | https://arxiv.org/abs/2601.07376 | Academic Papers | svg |
23bb11e316472017a4e1c50a09cd7622f6282ee66c81823acfbd54dcc2638195 | 2026-01-13T00:00:00-05:00 | Learning Dynamic Collaborative Network for Semi-supervised 3D Vessel Segmentation | arXiv:2601.07377v1 Announce Type: new Abstract: In this paper, we present a new dynamic collaborative network for semi-supervised 3D vessel segmentation, termed DiCo. Conventional mean teacher (MT) methods typically employ a static approach, where the roles of the teacher and student models are fixed. However, due to t... | https://arxiv.org/abs/2601.07377 | Academic Papers | svg |
e6ba663e276eafa6ed9946631c4be64a6659ed0e3950de1d3c1bd073e86e163a | 2026-01-13T00:00:00-05:00 | Interactive visualizations for adolescents to understand and challenge algorithmic profiling in online platforms | arXiv:2601.07381v1 Announce Type: new Abstract: Social media platforms regularly track, aggregate, and monetize adolescents' data, yet provide them with little visibility or agency over how algorithms construct their digital identities and make inferences about them. We introduce Algorithmic Mirror, an interactive visu... | https://arxiv.org/abs/2601.07381 | Academic Papers | svg |
910c32e3a1700a222a5d0513bf3f303a058dea2d638a77efc66fb23c80a90a74 | 2026-01-13T00:00:00-05:00 | CompNO: A Novel Foundation Model approach for solving Partial Differential Equations | arXiv:2601.07384v1 Announce Type: new Abstract: Partial differential equations (PDEs) govern a wide range of physical phenomena, but their numerical solution remains computationally demanding, especially when repeated simulations are required across many parameter settings. Recent Scientific Foundation Models (SFMs) ai... | https://arxiv.org/abs/2601.07384 | Academic Papers | svg |
70f59b9fdcbeee6c1adcb6381cc39e30ca9d9bdde9e70dadbf7a17f9e9767410 | 2026-01-13T00:00:00-05:00 | Computing patient similarity based on unstructured clinical notes | arXiv:2601.07385v1 Announce Type: new Abstract: Clinical notes hold rich yet unstructured details about diagnoses, treatments, and outcomes that are vital to precision medicine but hard to exploit at scale. We introduce a method that represents each patient as a matrix built from aggregated embeddings of all their note... | https://arxiv.org/abs/2601.07385 | Academic Papers | svg |
a97766792ab3f014dc31ed74a40cbd90bd4f632430ad5bd039e7b7d456b24bb2 | 2026-01-13T00:00:00-05:00 | Novel Decoding Algorithm for Noiseless Non-Adaptive Group Testing | arXiv:2601.07388v1 Announce Type: new Abstract: Group testing enables the identification of a small subset of defective items within a larger population by performing tests on pools of items rather than on each item individually. Over the years, it has not only attracted attention from the academic community, but has a... | https://arxiv.org/abs/2601.07388 | Academic Papers | svg |
887a6ee349f1375f27092fb89eb77a2cf9735e761e9eabc28a276e183ea1ac81 | 2026-01-13T00:00:00-05:00 | On the Non-decoupling of Supervised Fine-tuning and Reinforcement Learning in Post-training | arXiv:2601.07389v1 Announce Type: new Abstract: Post-training of large language models routinely interleaves supervised fine-tuning (SFT) with reinforcement learning (RL). These two methods have different objectives: SFT minimizes the cross-entropy loss between model outputs and expert responses, while RL maximizes rew... | https://arxiv.org/abs/2601.07389 | Academic Papers | svg |
e2299e5aaa14637e0816ab3536db813414070fe97fee24a8d13b6fa6d2e0f003 | 2026-01-13T00:00:00-05:00 | OceanSAR-2: A Universal Feature Extractor for SAR Ocean Observation | arXiv:2601.07392v1 Announce Type: new Abstract: We present OceanSAR-2, the second generation of our foundation model for SAR-based ocean observation. Building on our earlier release, which pioneered self-supervised learning on Sentinel-1 Wave Mode data, OceanSAR-2 relies on improved SSL training and dynamic data curati... | https://arxiv.org/abs/2601.07392 | Academic Papers | svg |
7209f6d9fd4a1db7ae7a6058ab1e71a84e2d88248b16473ab86a5b1ba6f3376d | 2026-01-13T00:00:00-05:00 | Software-Hardware Co-optimization for Modular E2E AV Paradigm: A Unified Framework of Optimization Approaches, Simulation Environment and Evaluation Metrics | arXiv:2601.07393v1 Announce Type: new Abstract: Modular end-to-end (ME2E) autonomous driving paradigms combine modular interpretability with global optimization capability and have demonstrated strong performance. However, existing studies mainly focus on accuracy improvement, while critical system-level factors such a... | https://arxiv.org/abs/2601.07393 | Academic Papers | svg |
21a8549913f3ab12915aa4c41ece17c5d515d0acbc5e5abc0d53f3b261afcb0a | 2026-01-13T00:00:00-05:00 | MCP-ITP: An Automated Framework for Implicit Tool Poisoning in MCP | arXiv:2601.07395v1 Announce Type: new Abstract: To standardize interactions between LLM-based agents and their environments, the Model Context Protocol (MCP) was proposed and has since been widely adopted. However, integrating external tools expands the attack surface, exposing agents to tool poisoning attacks. In such... | https://arxiv.org/abs/2601.07395 | Academic Papers | svg |
2063fa7d75f33018be1728180db3bf695bfd5ab8d920a38c781902df29706077 | 2026-01-13T00:00:00-05:00 | Forecast the Principal, Stabilize the Residual: Subspace-Aware Feature Caching for Efficient Diffusion Transformers | arXiv:2601.07396v1 Announce Type: new Abstract: Diffusion Transformer (DiT) models have achieved unprecedented quality in image and video generation, yet their iterative sampling process remains computationally prohibitive. To accelerate inference, feature caching methods have emerged by reusing intermediate representa... | https://arxiv.org/abs/2601.07396 | Academic Papers | svg |
68cdd3e150b44170e0c318848bcac72eaa5c16fc9f4e9fe88fb22b3b59363ab2 | 2026-01-13T00:00:00-05:00 | On Narrative: The Rhetorical Mechanisms of Online Polarisation | arXiv:2601.07398v1 Announce Type: new Abstract: Polarisation research has demonstrated how people cluster in homogeneous groups with opposing opinions. However, this effect emerges not only through interaction between people, limiting communication between groups, but also between narratives, shaping opinions and parti... | https://arxiv.org/abs/2601.07398 | Academic Papers | svg |
ebfddea9ecff92abb91cb912362ced5e8cf22884822379a10abf3afdc5394095 | 2026-01-13T00:00:00-05:00 | Recommendation-as-Experience: A framework for context-sensitive adaptation in conversational recommender systems | arXiv:2601.07401v1 Announce Type: new Abstract: While Conversational Recommender Systems (CRS) have matured technically, they frequently lack principled methods for encoding latent experiential aims as adaptive state variables. Consequently, contemporary architectures often prioritise ranking accuracy at the expense of... | https://arxiv.org/abs/2601.07401 | Academic Papers | svg |
ea4fe522ced38e9507b89d7d7dea32b3931ee524e9a536367917e5d07a38c283 | 2026-01-13T00:00:00-05:00 | Peacock: UEFI Firmware Runtime Observability Layer for Detection and Response | arXiv:2601.07402v1 Announce Type: new Abstract: Modern computing platforms rely on the Unified Extensible Firmware Interface (UEFI) to initialize hardware and coordinate the transition to the operating system. Because this execution environment operates with high privileges and persists across reboots, it has increasin... | https://arxiv.org/abs/2601.07402 | Academic Papers | svg |
8140c5746aacb0229fe349c82a02afa5f25f15ad6a309e258451abb8bd1ed34d | 2026-01-13T00:00:00-05:00 | Outcome-Grounded Advantage Reshaping for Fine-Grained Credit Assignment in Mathematical Reasoning | arXiv:2601.07408v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has emerged as a promising critic-free reinforcement learning paradigm for reasoning tasks. However, standard GRPO employs a coarse-grained credit assignment mechanism that propagates group-level rewards uniformly to to every toke... | https://arxiv.org/abs/2601.07408 | Academic Papers | svg |
8915fa820af7ca0db5581296552a22e19b5242e86744b2a355a85f4edf1a9177 | 2026-01-13T00:00:00-05:00 | SCALPEL: Selective Capability Ablation via Low-rank Parameter Editing for Large Language Model Interpretability Analysis | arXiv:2601.07411v1 Announce Type: new Abstract: Large language models excel across diverse domains, yet their deployment in healthcare, legal systems, and autonomous decision-making remains limited by incomplete understanding of their internal mechanisms. As these models integrate into high-stakes systems, understandin... | https://arxiv.org/abs/2601.07411 | Academic Papers | svg |
f5d467b3e1aa02e8837815423b95cc6020afc91f534d373188767ce3bfedf4fd | 2026-01-13T00:00:00-05:00 | The Practicality of Normalizing Flow Test-Time Training in Bayesian Inference for Agent-Based Models | arXiv:2601.07413v1 Announce Type: new Abstract: Agent-Based Models (ABMs) are gaining great popularity in economics and social science because of their strong flexibility to describe the realistic and heterogeneous decisions and interaction rules between individual agents. In this work, we investigate for the first tim... | https://arxiv.org/abs/2601.07413 | Academic Papers | svg |
6fbba68be4f57925e2f09070f74d704e471fcae33e817eb6e19321cef4c98cd9 | 2026-01-13T00:00:00-05:00 | PLANET v2.0: A comprehensive Protein-Ligand Affinity Prediction Model Based on Mixture Density Network | arXiv:2601.07415v1 Announce Type: new Abstract: Drug discovery represents a time-consuming and financially intensive process, and virtual screening can accelerate it. Scoring functions, as one of the tools guiding virtual screening, have their precision closely tied to screening efficiency. In our previous study, we de... | https://arxiv.org/abs/2601.07415 | Academic Papers | svg |
eb316ca2aa4586f96f44be30b2ffe59afd03f8ecd1ae230d147a0da5d8e252ff | 2026-01-13T00:00:00-05:00 | SDHSI-Net: Learning Better Representations for Hyperspectral Images via Self-Distillation | arXiv:2601.07416v1 Announce Type: new Abstract: Hyperspectral image (HSI) classification presents unique challenges due to its high spectral dimensionality and limited labeled data. Traditional deep learning models often suffer from overfitting and high computational costs. Self-distillation (SD), a variant of knowledg... | https://arxiv.org/abs/2601.07416 | Academic Papers | svg |
7d1950b372a084d96f0d074a0eaddc2f8ba2d31303821789b86d252391455f62 | 2026-01-13T00:00:00-05:00 | Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations | arXiv:2601.07422v1 Announce Type: new Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal states encode rich signals of truthfulness, yet the origins and mechanisms of these signals remain unclear. In this paper, we de... | https://arxiv.org/abs/2601.07422 | Academic Papers | svg |
fe48c3ddf43b72b0c64a9cc9dae2fdf901a2374fe5a3236127e71ac7ddd1b624 | 2026-01-13T00:00:00-05:00 | SAD: A Large-Scale Strategic Argumentative Dialogue Dataset | arXiv:2601.07423v1 Announce Type: new Abstract: Argumentation generation has attracted substantial research interest due to its central role in human reasoning and decision-making. However, most existing argumentative corpora focus on non-interactive, single-turn settings, either generating arguments from a given topic... | https://arxiv.org/abs/2601.07423 | Academic Papers | svg |
e93abeae1f67e452b928e50e830d191d8bf8831b61f036fe2b8e8969d14020fc | 2026-01-13T00:00:00-05:00 | Center-Fed Pinching Antenna System (C-PASS) Aided Wireless Communications | arXiv:2601.07424v1 Announce Type: new Abstract: The novel architecture of the center-fed pinching antenna system (C-PASS) is investigated, where the waveguide-fed signal is divided into two propagation directions through controllable power splitting. By doing so, a doubled degree of freedom (DoF) is achieved compared t... | https://arxiv.org/abs/2601.07424 | Academic Papers | svg |
13e5cbc1b2505bd4eae101e5b86fcda6caa1f4fb1606d9360dedda46567ae756 | 2026-01-13T00:00:00-05:00 | KALE: Enhancing Knowledge Manipulation in Large Language Models via Knowledge-aware Learning | arXiv:2601.07430v1 Announce Type: new Abstract: Despite the impressive performance of large language models (LLMs) pretrained on vast knowledge corpora, advancing their knowledge manipulation-the ability to effectively recall, reason, and transfer relevant knowledge-remains challenging. Existing methods mainly leverage... | https://arxiv.org/abs/2601.07430 | Academic Papers | svg |
6bdb3ce0d23f5ba7556ff8c67fc733546f3cb3a86e098b2190cd60f1512f4d9b | 2026-01-13T00:00:00-05:00 | LOONG: Online Time-Optimal Autonomous Flight for MAVs in Cluttered Environments | arXiv:2601.07434v1 Announce Type: new Abstract: Autonomous flight of micro air vehicles (MAVs) in unknown, cluttered environments remains challenging for time-critical missions due to conservative maneuvering strategies. This article presents an integrated planning and control framework for high-speed, time-optimal aut... | https://arxiv.org/abs/2601.07434 | Academic Papers | svg |
1cf27e18cc81378fe763167875b887750da6d8ebb240ac9f569ae3460fc99d0e | 2026-01-13T00:00:00-05:00 | Variational Autoencoder with Normalizing flow for X-ray spectral fitting | arXiv:2601.07440v1 Announce Type: new Abstract: Black hole X-ray binaries (BHBs) can be studied with spectral fitting to provide physical constraints on accretion in extreme gravitational environments. Traditional methods of spectral fitting such as Markov Chain Monte Carlo (MCMC) face limitations due to computational ... | https://arxiv.org/abs/2601.07440 | Academic Papers | svg |
d13e847c8f7782596bf961b8a63522858edb0708e6726cf3aacab8b9f9e2a532 | 2026-01-13T00:00:00-05:00 | Surrogate-based Optimization via Clustering for Box-Constrained Problems | arXiv:2601.07442v1 Announce Type: new Abstract: Global optimization of large-scale, complex systems such as multi-physics black-box simulations and real-world industrial systems is important but challenging. This work presents a novel Surrogate-Based Optimization framework based on Clustering, SBOC for global optimizat... | https://arxiv.org/abs/2601.07442 | Academic Papers | svg |
1261ff204f87f446a03354946dab651c9a6e7c9046e3846dff2a6ae9a242ce38 | 2026-01-13T00:00:00-05:00 | Formalization of Amicable Numbers Theory | arXiv:2601.07444v1 Announce Type: new Abstract: This paper presents a formalization of the theory of amicable numbers in the Lean~4 proof assistant. Two positive integers $m$ and $n$ are called an amicable pair if the sum of proper divisors of $m$ equals $n$ and the sum of proper divisors of $n$ equals $m$. Our formali... | https://arxiv.org/abs/2601.07444 | Academic Papers | svg |
6c4f1f300f631cfd4caf859f9d44ffc7af1e36c43582566163011f4bd9bfe4bd | 2026-01-13T00:00:00-05:00 | PanoSAMic: Panoramic Image Segmentation from SAM Feature Encoding and Dual View Fusion | arXiv:2601.07447v1 Announce Type: new Abstract: Existing image foundation models are not optimized for spherical images having been trained primarily on perspective images. PanoSAMic integrates the pre-trained Segment Anything (SAM) encoder to make use of its extensive training and integrate it into a semantic segmenta... | https://arxiv.org/abs/2601.07447 | Academic Papers | svg |
3045a6156274c9d6bc456ce161d17617d742ba8f28c4aecbfa7da58244a0e79a | 2026-01-13T00:00:00-05:00 | RLPO: Residual Listwise Preference Optimization for Long-Context Review Ranking | arXiv:2601.07449v1 Announce Type: new Abstract: Review ranking is pivotal in e-commerce for prioritizing diagnostic and authentic feedback from the deluge of user-generated content. While large language models have improved semantic assessment, existing ranking paradigms face a persistent trade-off in long-context sett... | https://arxiv.org/abs/2601.07449 | Academic Papers | svg |
57b52c2e8e33f342d3e9356da950a25bee58da169b14223ddf4a18715bb39884 | 2026-01-13T00:00:00-05:00 | Building Faculty Expertise Ontology using Protege: Enhancing Academic Library Research Services | arXiv:2601.07451v1 Announce Type: new Abstract: Academic libraries struggle to find and access faculty expertise across disciplines. This research proposes a faculty expertise ontology with a hierarchical structure based on Prot\'eg\'e to enhance library services and knowledge organisation. The ontology classifies rela... | https://arxiv.org/abs/2601.07451 | Academic Papers | svg |
1794e959d1f2ec9dcf121b6deef16a6ae951aedf64ae72b7d7c35dee891541fc | 2026-01-13T00:00:00-05:00 | WaveMan: mmWave-Based Room-Scale Human Interaction Perception for Humanoid Robots | arXiv:2601.07454v1 Announce Type: new Abstract: Reliable humanoid-robot interaction (HRI) in household environments is constrained by two fundamental requirements, namely robustness to unconstrained user positions and preservation of user privacy. Millimeter-wave (mmWave) sensing inherently supports privacy-preserving ... | https://arxiv.org/abs/2601.07454 | Academic Papers | svg |
f1f6a54e5bf8570a3aa396428270e3e7de44dec17c3ebeccc37ec154822e4ef7 | 2026-01-13T00:00:00-05:00 | TriCG with deflated restarting for symmetric quasi-definite linear systems | arXiv:2601.07455v1 Announce Type: new Abstract: TriCG is a short-recurrence iterative method recently introduced by Montoison and Orban [SIAM J. Sci. Comput., 43 (2021), pp. A2502--A2525] for solving symmetric quasi-definite (SQD) linear systems. TriCG takes advantage of the inherent block structure of SQD linear syste... | https://arxiv.org/abs/2601.07455 | Academic Papers | svg |
1bd51c5408738d9a42066a145721c6f22c92066ec1e271daf15f8323e4d296fb | 2026-01-13T00:00:00-05:00 | Improving Video Question Answering through query-based frame selection | arXiv:2601.07459v1 Announce Type: new Abstract: Video Question Answering (VideoQA) models enhance understanding and interaction with audiovisual content, making it more accessible, searchable, and useful for a wide range of fields such as education, surveillance, entertainment, and content creation. Due to heavy comput... | https://arxiv.org/abs/2601.07459 | Academic Papers | svg |
434b92d2cc0a01091459dc8047acfa6178d4a1afa992a725559e7c209bd477d3 | 2026-01-13T00:00:00-05:00 | From Sketch to Fresco: Efficient Diffusion Transformer with Progressive Resolution | arXiv:2601.07462v1 Announce Type: new Abstract: Diffusion Transformers achieve impressive generative quality but remain computationally expensive due to iterative sampling. Recently, dynamic resolution sampling has emerged as a promising acceleration technique by reducing the resolution of early sampling steps. However... | https://arxiv.org/abs/2601.07462 | Academic Papers | svg |
43f83654b19241223688916b66c1b78d7361582707011efb158ce11970edcfeb | 2026-01-13T00:00:00-05:00 | Puzzle it Out: Local-to-Global World Model for Offline Multi-Agent Reinforcement Learning | arXiv:2601.07463v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) aims to solve cooperative decision-making problems in multi-agent systems using pre-collected datasets. Existing offline MARL methods primarily constrain training within the dataset distribution, resulting in overly conser... | https://arxiv.org/abs/2601.07463 | Academic Papers | svg |
b7748c876455d002bc08f37e9bc4972a39d0929d06cf54671581aac27b6440cc | 2026-01-13T00:00:00-05:00 | IFDNS: An Iterative Feedback-Driven Neuro-Symbolic Method for Faithful Logical Reasoning | arXiv:2601.07464v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated impressive capabilities across a wide range of reasoning tasks, including logical and mathematical problem-solving. While prompt-based methods like Chain-of-Thought (CoT) can enhance LLM reasoning abilities to some extent, th... | https://arxiv.org/abs/2601.07464 | Academic Papers | svg |
4e5f2bbca6da09dc31dba8ab2c8708501c143c568cf6cd41409b3d855dea091c | 2026-01-13T00:00:00-05:00 | A Scalable Solution for Node Mobility Problems in NDN-Based Massive LEO Constellations | arXiv:2601.07466v1 Announce Type: new Abstract: In recent years, there has been increasing investment in the deployment of massive commercial Low Earth Orbit (LEO) constellations to provide global Internet connectivity. These constellations, now equipped with inter-satellite links, can serve as low-latency Internet bac... | https://arxiv.org/abs/2601.07466 | Academic Papers | svg |
fb68030d40a6676437e9e26ef11d385b996b1d7d778d2fad695d1773e2938362 | 2026-01-13T00:00:00-05:00 | Beyond Dialogue Time: Temporal Semantic Memory for Personalized LLM Agents | arXiv:2601.07468v1 Announce Type: new Abstract: Memory enables Large Language Model (LLM) agents to perceive, store, and use information from past dialogues, which is essential for personalization. However, existing methods fail to properly model the temporal dimension of memory in two aspects: 1) Temporal inaccuracy: ... | https://arxiv.org/abs/2601.07468 | Academic Papers | svg |
17dc3d88d022619c065f9b9e94df578916649c4ec8f8132b7f13d154e2b921b4 | 2026-01-13T00:00:00-05:00 | Knowledge Distillation for LLM-Based Human Activity Recognition in Homes | arXiv:2601.07469v1 Announce Type: new Abstract: Human Activity Recognition (HAR) is a central problem for context-aware applications, especially for smart homes and assisted living. A few very recent studies have shown that Large Language Models (LLMs) can be used for HAR at home, reaching high performance and addressi... | https://arxiv.org/abs/2601.07469 | Academic Papers | svg |
5cfe7b8907af2f18c574186f83324ce1d8e4833f03415ea0bb1dad02db9202d5 | 2026-01-13T00:00:00-05:00 | Learning How to Remember: A Meta-Cognitive Management Method for Structured and Transferable Agent Memory | arXiv:2601.07470v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on accumulated memory to solve long-horizon decision-making tasks. However, most existing approaches store memory in fixed representations and reuse it at a single or implicit level of abstraction, which limits generaliz... | https://arxiv.org/abs/2601.07470 | Academic Papers | svg |
bd8863cf5cb80672809eb664b11551dce5d32028c208ab4ba0aae956b15e1ff6 | 2026-01-13T00:00:00-05:00 | Secure Joint Source-Channel Coding for the AWGN Channel with Feedback: A Finite Blocklength Analysis | arXiv:2601.07472v1 Announce Type: new Abstract: In the literature, it has been shown that the secrecy capacity of the additive white Gaussian noise (AWGN) wiretap channel with noise-free feedback equals the capacity of the same model without secrecy constraint, and the classical Schalkwijk-Kailath (SK) scheme achieves ... | https://arxiv.org/abs/2601.07472 | Academic Papers | svg |
42fa67b0be40a277fc5dce534a3b9036be549bbbd5d960166a85ab756365d67a | 2026-01-13T00:00:00-05:00 | AntiPaSTO: Self-Supervised Steering of Moral Reasoning | arXiv:2601.07473v1 Announce Type: new Abstract: As models grow more capable, human supervision breaks down: labels don't scale, outputs can be gamed, and training doesn't generalize. Scalable oversight requires steering methods that are internal, self-supervised, and transfer out-of-distribution; existing methods satis... | https://arxiv.org/abs/2601.07473 | Academic Papers | svg |
8f198b02009240bfe64251809828eeedeadae1599ac6d7c4db62f605296807cb | 2026-01-13T00:00:00-05:00 | Task Prototype-Based Knowledge Retrieval for Multi-Task Learning from Partially Annotated Data | arXiv:2601.07474v1 Announce Type: new Abstract: Multi-task learning (MTL) is critical in real-world applications such as autonomous driving and robotics, enabling simultaneous handling of diverse tasks. However, obtaining fully annotated data for all tasks is impractical due to labeling costs. Existing methods for part... | https://arxiv.org/abs/2601.07474 | Academic Papers | svg |
0b092c4f40290b3298596ffedc3de751fce30fc8a0b19bc8518080e48f76ce63 | 2026-01-13T00:00:00-05:00 | ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs | arXiv:2601.07475v1 Announce Type: new Abstract: The emergence of fine-grained numerical formats like NVFP4 presents new opportunities for efficient Large Language Model (LLM) inference. However, it is difficult to adapt existing Post-Training Quantization (PTQ) strategies to these formats: rotation-based methods compro... | https://arxiv.org/abs/2601.07475 | Academic Papers | svg |
56ac3b9225abc37cb6967e15f21602ad6088f30a32703c7e6efc72ca3c216071 | 2026-01-13T00:00:00-05:00 | NanoCockpit: Performance-optimized Application Framework for AI-based Autonomous Nanorobotics | arXiv:2601.07476v1 Announce Type: new Abstract: Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad applicability and pushing scientific advancement on resource-limited embedded systems. Their small form factor, i.e., a few... | https://arxiv.org/abs/2601.07476 | Academic Papers | svg |
ef86b8b8035f20c28a1d97658945cf37767373f5b627764ebf761ee12c329c99 | 2026-01-13T00:00:00-05:00 | JudgeFlow: Agentic Workflow Optimization via Block Judge | arXiv:2601.07477v1 Announce Type: new Abstract: Optimizing LLM-based agentic workflows is challenging for scaling AI capabilities. Current methods rely on coarse, end-to-end evaluation signals and lack fine-grained signals on where to refine, often resulting in inefficient or low-impact modifications. To address these ... | https://arxiv.org/abs/2601.07477 | Academic Papers | svg |
52d911eb4b83ce590b39bbdba5d45ad54cb2d74491e93e5b05f152f0584cc357 | 2026-01-13T00:00:00-05:00 | Derivative-free discrete gradient methods | arXiv:2601.07479v1 Announce Type: new Abstract: Discrete gradient methods are a class of numerical integrators producing solutions with exact preservation of first integrals of ordinary differential equations. In this paper, we apply order theory combined with the symmetrized Itoh--Abe discrete gradient and finite diff... | https://arxiv.org/abs/2601.07479 | Academic Papers | svg |
ee50bfc238bd94d4a77896e4fd06e91329bd2a14cec4f30cec64ab9d1dd02cbb | 2026-01-13T00:00:00-05:00 | The Secretary Problem with Predictions and a Chosen Order | arXiv:2601.07482v1 Announce Type: new Abstract: We study a learning-augmented variant of the secretary problem, recently introduced by Fujii and Yoshida (2023), in which the decision-maker has access to machine-learned predictions of candidate values. The central challenge is to balance consistency and robustness: when... | https://arxiv.org/abs/2601.07482 | Academic Papers | svg |
19067fb3d4fc9123017b87103346c1b732e3b08013841d29a65151025e3e3c0d | 2026-01-13T00:00:00-05:00 | FocalOrder: Focal Preference Optimization for Reading Order Detection | arXiv:2601.07483v1 Announce Type: new Abstract: Reading order detection is the foundation of document understanding. Most existing methods rely on uniform supervision, implicitly assuming a constant difficulty distribution across layout regions. In this work, we challenge this assumption by revealing a critical flaw: \... | https://arxiv.org/abs/2601.07483 | Academic Papers | svg |
b38d31cfb389cbb121cb55a29d477a22f0d4569a9f00f0af06ff92c529eeba7b | 2026-01-13T00:00:00-05:00 | R3-RECON: Radiance-Field-Free Active Reconstruction via Renderability | arXiv:2601.07484v1 Announce Type: new Abstract: In active reconstruction, an embodied agent must decide where to look next to efficiently acquire views that support high-quality novel-view rendering. Recent work on active view planning for neural rendering largely derives next-best-view (NBV) criteria by backpropagatin... | https://arxiv.org/abs/2601.07484 | Academic Papers | svg |
585d96a82c64e2cc6c20641f20af85e397f7b4cd8fc1458d57f6475929397ba0 | 2026-01-13T00:00:00-05:00 | Frequency-Adaptive Multi-Band Architecture for Upper Mid-Band MIMO Systems | arXiv:2601.07489v1 Announce Type: new Abstract: FR3 ($\approx$7-24 GHz), also referred to as the upper mid-band, has recently emerged as promising spectrum for 6G; however, its propagation and MIMO characteristics vary significantly with frequency and environment, and spectrum availability may be intermittent due to in... | https://arxiv.org/abs/2601.07489 | Academic Papers | svg |
61e51e0b2bc09147d366d7bb4c54d8483ed7ffe3be28e50a070d80a39878ae79 | 2026-01-13T00:00:00-05:00 | Graph Inference Towards ICD Coding | arXiv:2601.07496v1 Announce Type: new Abstract: Automated ICD coding involves assigning standardized diagnostic codes to clinical narratives. The vast label space and extreme class imbalance continue to challenge precise prediction. To address these issues, LabGraph is introduced -- a unified framework that reformulate... | https://arxiv.org/abs/2601.07496 | Academic Papers | svg |
9f7ea43bf7a7dc0d32109219ec9c14c9df2ef3ea980696d22d3fe299ef2167e0 | 2026-01-13T00:00:00-05:00 | On spectral properties and fast initial convergence of the Kaczmarz method | arXiv:2601.07498v1 Announce Type: new Abstract: The Kaczmarz method is successfully used for solving discretizations of linear inverse problems, especially in computed tomography where it is known as ART. Practitioners often observe and appreciate its fast convergence in the first few iterations, leading to the same fa... | https://arxiv.org/abs/2601.07498 | Academic Papers | svg |
5615d408f8a4f9f4801471928200b2bd01cc48252608737c1297710003e54700 | 2026-01-13T00:00:00-05:00 | Anatomy Aware Cascade Network: Bridging Epistemic Uncertainty and Geometric Manifold for 3D Tooth Segmentation | arXiv:2601.07499v1 Announce Type: new Abstract: Accurate three-dimensional (3D) tooth segmentation from Cone-Beam Computed Tomography (CBCT) is a prerequisite for digital dental workflows. However, achieving high-fidelity segmentation remains challenging due to adhesion artifacts in naturally occluded scans, which are ... | https://arxiv.org/abs/2601.07499 | Academic Papers | svg |
f6e59a288013b6e631996d0f3f6bcadd6b001b101fbe1994f091261e979e1035 | 2026-01-13T00:00:00-05:00 | FROAV: A Framework for RAG Observation and Agent Verification - Lowering the Barrier to LLM Agent Research | arXiv:2601.07504v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) and their integration into autonomous agent systems has created unprecedented opportunities for document analysis, decision support, and knowledge retrieval. However, the complexity of developing, evaluating, and itera... | https://arxiv.org/abs/2601.07504 | Academic Papers | svg |
5833516b9971d9bc44dde4fcfa50ec9b327d0549103cae26e0813f03f5141adc | 2026-01-13T00:00:00-05:00 | Judging Against the Reference: Uncovering Knowledge-Driven Failures in LLM-Judges on QA Evaluation | arXiv:2601.07506v1 Announce Type: new Abstract: While large language models (LLMs) are increasingly used as automatic judges for question answering (QA) and other reference-conditioned evaluation tasks, little is known about their ability to adhere to a provided reference. We identify a critical failure mode of such re... | https://arxiv.org/abs/2601.07506 | Academic Papers | svg |
d06adec51fc8e85fe3b020669b979540110ffc49b14255ea2f198dd910448e7a | 2026-01-13T00:00:00-05:00 | High-Rank Structured Modulation for Parameter-Efficient Fine-Tuning | arXiv:2601.07507v1 Announce Type: new Abstract: As the number of model parameters increases, parameter-efficient fine-tuning (PEFT) has become the go-to choice for tailoring pre-trained large language models. Low-rank Adaptation (LoRA) uses a low-rank update method to simulate full parameter fine-tuning, which is widel... | https://arxiv.org/abs/2601.07507 | Academic Papers | svg |
464bd60c3a6d3d98ed7d242becc23581d6fc983e4685f8714d7366966be7b5e8 | 2026-01-13T00:00:00-05:00 | Multiword matrix multiplication over large finite fields in floating-point arithmetic | arXiv:2601.07508v1 Announce Type: new Abstract: This article is concerned with the efficient computation of modular matrix multiplication C=AB mod p, a key kernel in computer algebra. We focus on floating-point arithmetic, which allows for using efficient matrix multiplication libraries. However, the existing approach ... | https://arxiv.org/abs/2601.07508 | Academic Papers | svg |
d12766a8a7759bed0936b09104a5d8e2caf25563fb664fd59c25910dd99e46c5 | 2026-01-13T00:00:00-05:00 | Machine Learning Model Trading with Verification under Information Asymmetry | arXiv:2601.07510v1 Announce Type: new Abstract: Machine learning (ML) model trading, known for its role in protecting data privacy, faces a major challenge: information asymmetry. This issue can lead to model deception, a problem that current literature has not fully solved, where the seller misrepresents model perform... | https://arxiv.org/abs/2601.07510 | Academic Papers | svg |
cb85208ddfd49ad825d4ae983ce6cb757cade35869377f16085902c2ae13b4ab | 2026-01-13T00:00:00-05:00 | Principal ideal problem and ideal shortest vector over rational primes in power-of-two cyclotomic fields | arXiv:2601.07511v1 Announce Type: new Abstract: The shortest vector problem (SVP) over ideal lattices is closely related to the Ring-LWE problem, which is widely used to build post-quantum cryptosystems. Power-of-two cyclotomic fields are frequently adopted to instantiate Ring-LWE. Pan et al. (EUROCRYPT~2021) explored ... | https://arxiv.org/abs/2601.07511 | Academic Papers | svg |
a0d2902a7192fa3ee60c427f76ef195f325102753c778567dac5d84c22f28d25 | 2026-01-13T00:00:00-05:00 | Land-then-transport: A Flow Matching-Based Generative Decoder for Wireless Image Transmission | arXiv:2601.07512v1 Announce Type: new Abstract: Due to strict rate and reliability demands, wireless image transmission remains difficult for both classical layered designs and joint source-channel coding (JSCC), especially under low latency. Diffusion-based generative decoders can deliver strong perceptual quality by ... | https://arxiv.org/abs/2601.07512 | Academic Papers | svg |
0a0faf4036b7ec238114dd003f287e20cc529ec4adb9d525e3075faeeb29fd7b | 2026-01-13T00:00:00-05:00 | A Parity-Consistent Decomposition Method for the Weight Distribution of Pre-Transformed Polar Codes | arXiv:2601.07515v1 Announce Type: new Abstract: This paper introduces an efficient algorithm based on the Parity-Consistent Decomposition (PCD) method to determine the WD of pre-transformed polar codes. First, to address the bit dependencies introduced by the pre-transformation matrix, we propose an iterative algorithm... | https://arxiv.org/abs/2601.07515 | Academic Papers | svg |
efdbe4e0c52db97dfe648b08a305f2bd9ee0236386cff5be5eb95cf7a64aa294 | 2026-01-13T00:00:00-05:00 | Controlling Multimodal Conversational Agents with Coverage-Enhanced Latent Actions | arXiv:2601.07516v1 Announce Type: new Abstract: Vision-language models are increasingly employed as multimodal conversational agents (MCAs) for diverse conversational tasks. Recently, reinforcement learning (RL) has been widely explored for adapting MCAs to various human-AI interaction scenarios. Despite showing great ... | https://arxiv.org/abs/2601.07516 | Academic Papers | svg |
fb333672caeaef7a8afb92fad915de58dc47040b4063af3f0f4deb10d2865ca9 | 2026-01-13T00:00:00-05:00 | Mon3tr: Monocular 3D Telepresence with Pre-built Gaussian Avatars as Amortization | arXiv:2601.07518v1 Announce Type: new Abstract: Immersive telepresence aims to transform human interaction in AR/VR applications by enabling lifelike full-body holographic representations for enhanced remote collaboration. However, existing systems rely on hardware-intensive multi-camera setups and demand high bandwidt... | https://arxiv.org/abs/2601.07518 | Academic Papers | svg |
637a0cd54b54b60472a8c004ad58693786d5650f3b5623f10748dc38a436e9df | 2026-01-13T00:00:00-05:00 | Sparse Point-wise Privacy Leakage: Mechanism Design and Fundamental Limits | arXiv:2601.07523v1 Announce Type: new Abstract: We study an information-theoretic privacy mechanism design problem, where an agent observes useful data $Y$ that is arbitrarily correlated with sensitive data $X$, and design disclosed data $U$ generated from $Y$ (the agent has no direct access to $X$). We introduce \emph... | https://arxiv.org/abs/2601.07523 | Academic Papers | svg |
5c218c09a0be16e7d1a14d9ab8a3fab8e54dee89016ce6691061c4067452864f | 2026-01-13T00:00:00-05:00 | Stagewise Reinforcement Learning and the Geometry of the Regret Landscape | arXiv:2601.07524v1 Announce Type: new Abstract: Singular learning theory characterizes Bayesian learning as an evolving tradeoff between accuracy and complexity, with transitions between qualitatively different solutions as sample size increases. We extend this theory to deep reinforcement learning, proving that the co... | https://arxiv.org/abs/2601.07524 | Academic Papers | svg |
9a9d7b0640190eff6f14cb1308741c7507765ffcbba429068966acf90158c752 | 2026-01-13T00:00:00-05:00 | Thinking Before Constraining: A Unified Decoding Framework for Large Language Models | arXiv:2601.07525v1 Announce Type: new Abstract: Natural generation allows Language Models (LMs) to produce free-form responses with rich reasoning, but the lack of guaranteed structure makes outputs difficult to parse or verify. Structured generation, or constrained decoding, addresses this drawback by producing conten... | https://arxiv.org/abs/2601.07525 | Academic Papers | svg |
999e816ae52e3fdd94b82435d319fb6aae1a6c7099b14b75c8da8fd801127cd3 | 2026-01-13T00:00:00-05:00 | MegaFlow: Large-Scale Distributed Orchestration System for the Agentic Era | arXiv:2601.07526v1 Announce Type: new Abstract: The rapid development of interactive and autonomous AI systems signals our entry into the agentic era. Training and evaluating agents on complex agentic tasks such as software engineering and computer use requires not only efficient model computation but also sophisticate... | https://arxiv.org/abs/2601.07526 | Academic Papers | svg |
644cc0ebf5cbdc0a1286f0a08e68fdee1d3f65aa9e9123f7944e677d0e9a4b04 | 2026-01-13T00:00:00-05:00 | Energy-efficient torque allocation for straight-line driving of electric vehicles based on pseudoconvex polynomials | arXiv:2601.07527v1 Announce Type: new Abstract: Electric vehicles with multiple motors provide a flexibility in meeting the driver torque demand, which calls for minimizing the battery energy consumption through torque allocation. In this paper, we present an approach to this problem based on approximating electric mot... | https://arxiv.org/abs/2601.07527 | Academic Papers | svg |
82fd68d31e5c4d3ef4581e84b7b54fa9ab158a8cdd6a87c62d12ac83a3d36783 | 2026-01-13T00:00:00-05:00 | From RAG to Agentic RAG for Faithful Islamic Question Answering | arXiv:2601.07528v1 Announce Type: new Abstract: LLMs are increasingly used for Islamic question answering, where ungrounded responses may carry serious religious consequences. Yet standard MCQ/MRC-style evaluations do not capture key real-world failure modes, notably free-form hallucinations and whether models appropri... | https://arxiv.org/abs/2601.07528 | Academic Papers | svg |
7b9de74c82c3639fc672d40a38aa05b4b15f48e3c32b030c66b5a8fe9887f263 | 2026-01-13T00:00:00-05:00 | Loci Similes: A Benchmark for Extracting Intertextualities in Latin Literature | arXiv:2601.07533v1 Announce Type: new Abstract: Tracing connections between historical texts is an important part of intertextual research, enabling scholars to reconstruct the virtual library of a writer and identify the sources influencing their creative process. These intertextual links manifest in diverse forms, ra... | https://arxiv.org/abs/2601.07533 | Academic Papers | svg |
3792ac5bd8aef399da90d847e0a0c5f7c60b5c6230c0b6fe4f9e6776e3680c39 | 2026-01-13T00:00:00-05:00 | A Protocol-Aware P4 Pipeline for MQTT Security and Anomaly Mitigation in Edge IoT Systems | arXiv:2601.07536v1 Announce Type: new Abstract: MQTT is the dominant lightweight publish--subscribe protocol for IoT deployments, yet edge security remains inadequate. Cloud-based intrusion detection systems add latency that is unsuitable for real-time control, while CPU-bound firewalls and generic SDN controllers lack... | https://arxiv.org/abs/2601.07536 | Academic Papers | svg |
7d1e0d55d030472933a675234e561dd88ddbffb44200d065bb4d32bb203883d1 | 2026-01-13T00:00:00-05:00 | FairRF: Multi-Objective Search for Single and Intersectional Software Fairness | arXiv:2601.07537v1 Announce Type: new Abstract: Background: The wide adoption of AI- and ML-based systems in sensitive domains raises severe concerns about their fairness. Many methods have been proposed in the literature to enhance software fairness. However, the majority behave as a black-box, not allowing stakeholde... | https://arxiv.org/abs/2601.07537 | Academic Papers | svg |
9567c1e8aca0602f4d67afefa0eab41a6ff7f277be17da7858ac1f3920e77cbd | 2026-01-13T00:00:00-05:00 | ViewMorpher3D: A 3D-aware Diffusion Framework for Multi-Camera Novel View Synthesis in Autonomous Driving | arXiv:2601.07540v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on multi-view images to ensure accurate perception and robust decision-making. To effectively develop and evaluate perception stacks and planning algorithms, realistic closed-loop simulators are indispensable. While 3D reconstructio... | https://arxiv.org/abs/2601.07540 | Academic Papers | svg |
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