A group G is locally finite precisely when every bijective cellular automaton A^G to A^G is reversible for every alphabet A.
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An extension of HybridSynchAADL and its application to collaborating au- tonomous UA Vs
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Closed-form solutions are provided for a family of nonconvex optimization problems on ratios of principal minor products for positive definite matrices, confirming the Ingleton ratio infimum is 16/27 for 4x4 matrices.
SuperDP refutes ε-DP via simultaneous synthesis of input pairs and witness functions using upper expectation supermartingales and lower expectation submartingales, delivering the first fully automated, sound, and semi-complete method applicable to both discrete and continuous stochastic mechanisms.
A survey of 172 open educational datasets from 204 papers across LAK, EDM, and AIED conferences reveals trends, 143 previously uncatalogued datasets, field gaps, and an 8-item PRACTICE checklist for better data publication.
HDL defines dynamic theories with lifting and combination operations, proves soundness and relative completeness in Isabelle, and demonstrates the approach on a Java controller steering a differential dynamic logic plant model.
RESOLVE provides a controlled multi-resolution LiDAR and camera benchmark for evaluating 3D detection and tracking under point sparsity variations in roadside cooperative perception.
Uniform Lyndon interpolation is shown for GLS via non-wellfounded proofs, closing a prior gap and yielding an alternative cut-elimination proof.
A regularization technique that treats diffusion model outputs as a similarity kernel during material optimization in inverse rendering, enabling joint reconstruction of geometry, materials, and illumination that satisfies the rendering equation and generalizes to new lighting.
For every fixed period k≥2, cyclic-attractor detection in Boolean networks is NP-complete exactly when local rules contain majority-like self-dual or mixed monotone AND-OR classes, and polynomial otherwise.
AirGroundBench is a new diagnostic benchmark exposing that MLLMs handle basic spatial perception but struggle with cross-view alignment, transformation reasoning, and embodied navigation under heterogeneous air-ground views.
Longitudinal measurement study finds limited and uneven adoption of Privacy Sandbox APIs across websites and Chrome users, yielding lessons and recommendations after the project's 2025 cancellation.
An argument paper reframes LLM explainability as an embodied, situated practice based on Dourish and enactivist cognition, identifying ontological obstacles in internal explanations and advocating affordance-based designs.
Orli is an autoregressive image-to-sequence model that jointly detects text lines and determines their reading order on historical documents via chord-frame baselines, trained on 196k pages across ten scripts.
A matched-pair protocol and Accurate Differentiation Rate metric reveal that conventional LLM accuracy on SAT problems is often inflated by over-predicting satisfiability, while cross-representation agreement exceeds 80 percent for most models.
Event-B Agent is an LLM agent that synthesizes, refines, and repairs Event-B formal models from natural language requirements via iterative verification feedback loops.
Quantum graphs are redefined as left ideals in the extended Haagerup tensor product, enabling representation-independent morphisms and categorical (co)limits.
Pulse-level parameterization of quantum Fourier models replaces single gate angles with multiple independent sub-angles, relaxing monomial couplings and improving gradient descent performance on Fourier series tasks.
ReformIR adaptively prioritizes reformulations and documents with a surrogate model guided by ranker feedback to boost recall while suppressing drift under fixed reranking budgets.
LeetProof achieves higher rates of fully certified program synthesis from natural language by using a multi-modal verifier in Lean to validate specifications via randomized testing and delegate proofs to AI tools, outperforming single-mode baselines on benchmarks while uncovering defects in prior参考.
SEED is a new benchmark for sequential provenance tracing in diffusion-edited deepfake faces, with the FAITH baseline showing that wavelet-based high-frequency signals aid detection of accumulated editing artifacts.
A Chrome extension provides no-code, serverless AI-assisted title and abstract screening for systematic reviews by integrating LLMs and ML active learning with Google Sheets.
FP64 tensor cores accelerate high-order finite-element kernels in MFEM by up to 2x with 83% energy gains and near-perfect weak scaling on exascale hardware.
Text Encoded Extrusions (TEE) lets LLMs generate and edit manifold 3D meshes by learning sequences of face extrusions from decomposed quadrilateral meshes.
Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
citing papers explorer
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A Reversibility Characterization of Locally Finite Groups by Cellular Automata
A group G is locally finite precisely when every bijective cellular automaton A^G to A^G is reversible for every alphabet A.
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Sharp Inequalities for Products of Principal Minors of Positive Definite Matrices
Closed-form solutions are provided for a family of nonconvex optimization problems on ratios of principal minor products for positive definite matrices, confirming the Ingleton ratio infimum is 16/27 for 4x4 matrices.
-
SuperDP: Differential Privacy Refutation via Supermartingales
SuperDP refutes ε-DP via simultaneous synthesis of input pairs and witness functions using upper expectation supermartingales and lower expectation submartingales, delivering the first fully automated, sound, and semi-complete method applicable to both discrete and continuous stochastic mechanisms.
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Open Datasets in Learning Analytics: Trends, Challenges, and Best PRACTICE
A survey of 172 open educational datasets from 204 papers across LAK, EDM, and AIED conferences reveals trends, 143 previously uncatalogued datasets, field gaps, and an 8-item PRACTICE checklist for better data publication.
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Heterogeneous Dynamic Logic: Provability Modulo Program Theories
HDL defines dynamic theories with lifting and combination operations, proves soundness and relative completeness in Isabelle, and demonstrates the approach on a Java controller steering a differential dynamic logic plant model.
-
RESOLVE: A Multi-Resolution and Multi-Modal Dataset for Roadside Cooperative Perception
RESOLVE provides a controlled multi-resolution LiDAR and camera benchmark for evaluating 3D detection and tracking under point sparsity variations in roadside cooperative perception.
-
Uniform Lyndon Interpolation via Non-wellfounded Proofs
Uniform Lyndon interpolation is shown for GLS via non-wellfounded proofs, closing a prior gap and yielding an alternative cut-elimination proof.
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Diffusion-Based Material Regularization for Physics-Based Inverse Rendering
A regularization technique that treats diffusion model outputs as a similarity kernel during material optimization in inverse rendering, enabling joint reconstruction of geometry, materials, and illumination that satisfies the rendering equation and generalizes to new lighting.
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A Complete Complexity Dichotomy for Cyclic Attractor Detection in Boolean Networks with Restricted Local Rules
For every fixed period k≥2, cyclic-attractor detection in Boolean networks is NP-complete exactly when local rules contain majority-like self-dual or mixed monotone AND-OR classes, and polynomial otherwise.
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AirGroundBench: Probing Spatial Intelligence in Multimodal Large Models under Heterogeneous Multi-View Embodied Collaboration
AirGroundBench is a new diagnostic benchmark exposing that MLLMs handle basic spatial perception but struggle with cross-view alignment, transformation reasoning, and embodied navigation under heterogeneous air-ground views.
-
Lessons from the Adoption and Deprecation of the Privacy Sandbox Web APIs
Longitudinal measurement study finds limited and uneven adoption of Privacy Sandbox APIs across websites and Chrome users, yielding lessons and recommendations after the project's 2025 cancellation.
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Embodied Explainability and Ontological Obstacles: Why We Struggle to Explain the Answers of Large Language Models (LLMs)
An argument paper reframes LLM explainability as an embodied, situated practice based on Dourish and enactivist cognition, identifying ontological obstacles in internal explanations and advocating affordance-based designs.
-
End-to-End Text Line Detection and Ordering
Orli is an autoregressive image-to-sequence model that jointly detects text lines and determines their reading order on historical documents via chord-frame baselines, trained on 196k pages across ten scripts.
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Satisfiability Solving with LLMs: A Matched-Pair Evaluation of Reasoning Capability
A matched-pair protocol and Accurate Differentiation Rate metric reveal that conventional LLM accuracy on SAT problems is often inflated by over-predicting satisfiability, while cross-representation agreement exceeds 80 percent for most models.
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Event-B Agent: Towards LLM Agent for Formal Model Synthesis and Repair
Event-B Agent is an LLM agent that synthesizes, refines, and repairs Event-B formal models from natural language requirements via iterative verification feedback loops.
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Categorical (Co)Limits of Quantum Graphs
Quantum graphs are redefined as left ideals in the extended Haagerup tensor product, enabling representation-independent morphisms and categorical (co)limits.
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Beyond Gates: Pulse Level Quantum Fourier Models
Pulse-level parameterization of quantum Fourier models replaces single gate angles with multiple independent sub-angles, relaxing monomial couplings and improving gradient descent performance on Fourier series tasks.
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When More Reformulations Hurt: Avoiding Drift using Ranker Feedback
ReformIR adaptively prioritizes reformulations and documents with a surrogate model guided by ranker feedback to boost recall while suppressing drift under fixed reranking budgets.
-
Certified Program Synthesis with a Multi-Modal Verifier
LeetProof achieves higher rates of fully certified program synthesis from natural language by using a multi-modal verifier in Lean to validate specifications via randomized testing and delegate proofs to AI tools, outperforming single-mode baselines on benchmarks while uncovering defects in prior参考.
-
SEED: A Large-Scale Benchmark for Provenance Tracing in Sequential Deepfake Facial Edits
SEED is a new benchmark for sequential provenance tracing in diffusion-edited deepfake faces, with the FAITH baseline showing that wavelet-based high-frequency signals aid detection of accumulated editing artifacts.
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TiAb Review Plugin: A Browser-Based Tool for AI-Assisted Title and Abstract Screening
A Chrome extension provides no-code, serverless AI-assisted title and abstract screening for systematic reviews by integrating LLMs and ML active learning with Google Sheets.
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Accelerating High-Order Finite Element Simulations at Extreme Scale with FP64 Tensor Cores
FP64 tensor cores accelerate high-order finite-element kernels in MFEM by up to 2x with 83% energy gains and near-perfect weak scaling on exascale hardware.
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Learning to Build Shapes by Extrusion
Text Encoded Extrusions (TEE) lets LLMs generate and edit manifold 3D meshes by learning sequences of face extrusions from decomposed quadrilateral meshes.
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Results-Actionability Gap: Understanding How Practitioners Evaluate LLM Products in the Wild
Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
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Centralization and Stability in Formal Constitutions
Only dictatorships are self-maintaining under i.i.d. unbiased beliefs with arbitrary tie-breaking, while rules with minimal winning coalitions of size at most 2 are stable under pessimistic beliefs and status-quo tie-breaking.
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A Composable Game-Theoretic Framework for Blockchains
Introduces the first compositional game-theoretic framework for blockchains using cross-layer games and cross-application composition to analyze incentive compatibility and reveal vulnerabilities in composed systems.
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On Propositional Dynamic Logic and Concurrency
Generalizes PDL to OPDL by distinguishing programs from traces via arbitrary operational semantics and proves cut-elimination for a non-wellfounded sequent calculus.
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A rewriting-logic-with-SMT-based formal analysis and parameter synthesis framework for parametric time Petri nets
A Maude-with-SMT framework for sound and complete formal analysis and parameter synthesis of parametric time Petri nets, including a folding approach that terminates on finite parametric state-class graphs and support for LTL model checking.
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An Effective Quantum Hoare Logic for Hybrid Quantum Programs with Unbounded Loops
Integer hybrid path-sums plus a sound Hoare logic enable semi-automated functional verification and expected-cost analysis of hybrid quantum programs with unbounded while loops.
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Evaluating Static and Process Evidence for Code Authorship in Programming Education
Repository-visible process features (commit timing, change volume, deadline distance) improve educational code authorship attribution from 0.094 to 0.233 top-1 and verification ROC-AUC from 0.556 to 0.752 across six matched comparisons, while contest data achieves 0.938 top-1.
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LV-ROVER-MLT: Low-Resource Maltese OCR by Synthetic Fine-Tuning and Multi-Stream Arbitration
Fine-tuning Tesseract on synthetic Maltese line images plus lexicon-gated arbitration of five recognizer streams reduces development-set CER from 0.0234 to 0.01317 (and 0.00700 with label normalization).
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UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion
A two-stage universal-then-specialize adapter with Morphable Attention Flow networks delivers SOTA FID/CLIP under single or composite conditioning at constant parameter and memory cost.
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Big-step and small-step Horn clause derivations applied to operational semantics
Proves equivalence of big-step and small-step Horn clause derivations and supplies a transformation to convert any clause set into one inheriting a chosen derivation behavior.
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Type-Error Ablation and AI Coding Agents
Ablation experiment in Shplait finds that detailed type error messages improve AI agents' type-error repair rates over minimal messages or dynamic errors, with type systems adding further benefit.
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Internally Referenced Low-Light Enhancement
Introduces self-supervised LLIE using internal low-frequency pseudo ground-truth, dual-domain structural constraints, and gain-adaptive modulation to achieve superior noise suppression and detail preservation.
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Guiding LLM-based Loop Invariant Synthesis via Feedback on Local Reasoning Errors
LORIS detects local reasoning errors in LLM-generated proofs for loop invariants by translating natural-language steps to first-order logic implications and using invalid implications to refine the invariants, achieving 93.1% success on 460 C programs.
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Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation
Decomposed Vision-Language Alignment framework factorizes prompts into concept and attribute tokens with Feature-Gated Cross-Attention for better compositional generalization in fine-grained open-vocabulary segmentation.
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Vector Scaffolding: Inter-Scale Orchestration for Differentiable Image Vectorization
Vector Scaffolding uses Interior Gradient Aggregation, Progressive Stratification, and Rapid Inflation Scheduling to achieve 2.5x faster optimization and up to 1.4 dB higher PSNR in differentiable image vectorization.
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On the Quantisation of Linear Gauge Theories on Lorentzian Manifolds: Maxwell's Theory via Complete Gauge Fixing
A new complete gauge fixing at initial data via Hodge decomposition on complete Riemannian manifolds enables existence proofs for Hadamard states in the quantization of Maxwell theory on globally hyperbolic Lorentzian manifolds.
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An Effective Orchestral Approach to Satisfiability Modulo Prime Fields
A new orchestral DPLL(T) approach for SMT over prime fields outperforms prior tools on ZKP compiler and circuit benchmarks by balancing completeness and efficiency across coordinated modules.
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SIEVES: Selective Prediction Generalizes through Visual Evidence Scoring
SIEVES improves selective prediction coverage by up to 3x on OOD VQA benchmarks by training a selector to score the quality of visual evidence produced by reasoner models, generalizing across benchmarks and proprietary models without internal access or per-task retraining.
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SAFEdit: Does Multi-Agent Decomposition Resolve the Reliability Challenges of Instructed Code Editing?
SAFEdit reaches 68.6% task success on EditBench code edits by using planner, editor, and verifier agents plus a failure abstraction layer, beating single-model and ReAct baselines.
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When AI reviews science: Can we trust the referee?
AI peer review systems are vulnerable to prompt injections, prestige biases, assertion strength effects, and contextual poisoning, as demonstrated by a new attack taxonomy and causal experiments on real conference submissions.
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Option Pricing on Noisy Intermediate-Scale Quantum Computers: A Quantum Neural Network Approach
A compact 2-qubit QNN approximates Black-Scholes-Merton option prices with usable accuracy when executed on multiple commercial NISQ quantum processors.
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Spectral-angular parametrization of open qudit dynamics
Density matrices are decomposed into spectral root coordinates r in the positive Weyl chamber and angular coordinates on SU(n)/T^{n-1}, yielding partial decoupling where only dissipation drives the spectral evolution under GKLS dynamics.
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Make it Simple, Make it Dance: Dance Motion Simplification to Support Novices' Dance Learning
Rule-based and learning-based algorithms simplify dance motions to help novices learn more effectively while maintaining naturalness and style.
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AnomalyAgent: Agentic Industrial Anomaly Synthesis via Tool-Augmented Reinforcement Learning
AnomalyAgent uses tool-augmented reinforcement learning with self-reflection to generate realistic industrial anomalies, achieving better metrics than zero-shot methods on MVTec-AD.
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Anytime Analysis on BinVal: Adaptive Parameters Help
Self-adjusting mutation rates let the (1+1) EA optimize the top k bits of BinVal in O(k^{1+ε}) time independent of n for all k in o(n) simultaneously.
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Context Matters: Evaluating Context Strategies for Automated ADR Generation Using LLMs
A small recency window of 3-5 prior ADRs as context produces higher-fidelity LLM-generated Architecture Decision Records than no context, full history, or retrieval-augmented selection in typical sequential workflows.
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First-order definability of Campana Points and Darmon Points in algebraic function fields in one variable over number fields
Establishes first-order definability of Campana and Darmon points in algebraic function fields over number fields by extending quadratic Pfister form methods from prior number field results.