Truncation

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Period ending 2026-09-14

1 new paper

A weekly snapshot of new work published in Truncation.

Period ending 2026-09-07

2 new papers

A weekly snapshot of new work published in Truncation.

32 papers

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Why Learning Rediscovers the Closed-Form Diagonal Regularizer
Sep 9, 2026Jeahn Han, Pyojin KimRegularization Methods Ill-Posed Inverse Problem
It's the Problem, Not the Path: Budget and Difficulty Confounds in LLM Reasoning Trajectories
Sep 3, 2026Yigit Utku BulutLLM Reasoning Methods Reasoning Traces
From Truncation to Commitment: Persistent Context in Uniform Discrete Diffusion
Sep 1, 2026Satoshi HayakawaDiffusion Sampling Truncation
Approximate Speculative Decoding
Aug 4, 2026Yuannuo Feng, Zegang Peng, Yuxin Xie +5Speculative Decoding Truncation
Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models
Aug 4, 2026Edgar Jaber, Rémy Vallot, Thibault Dairay +1Reduced-Order Models Uncertainty Quantification
Distractor-Aware Truncation: Disentangling Context-Length Effects from Signal Loss in Long-Context LLM Benchmarks
Aug 4, 2026Mohsen ArjmandiContext Length Retrieval Benchmarks
Floor, Ceiling, and the Fusion Gap: How Much of Crowd Reading Attention Can Machines Predict?
Aug 3, 2026Kazuki Nakayashiki, Keisuke WatanabeReading Ceiling
Revisiting Lossy Verification in Speculative Decoding: Mechanisms, Trade-offs, and Failure Modes
Jul 29, 2026Tianyu Wang, Yuxuan Zhou, Wenbin Wang +3Speculative Decoding LLM Inference Efficiency
Spectral Truncation in Synthetic Control
Jul 27, 2026Mojtaba EslamiSpectral Algorithms Heterogeneous Treatment Effects
Asymptotically Optimal Regret for Reinforcement Learning without Horizon Dependence
Jul 22, 2026Runlong Zhou, Zihan Zhang, Maryam Fazel +1Finite Planning Horizon Finite-Horizon Episodic Markov Decision Processes
Seeing the End at Step Zero: Accelerating Diffusion MLLMs via MLP Sparsity-Aware Truncation
Jul 16, 2026Qicheng Zhao, Qi Sun, Zheyu YanDiffusion Language Models LLM Inference Efficiency
Improving Sample Diversity in Autoregressive Text-to-Image Generation via Cluster Truncation
Jul 12, 2026Trang Nguyen, Shuang Wu, Runyan Tan +1Autoregressive Image Generation Text-To-Image
Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains
Jun 30, 2026Haixin Wang, Haoning Dang, Fei Wang +1Partial Differential Equations Solution Operator
Fast algorithms for learning a Gaussian under halfspace truncation with optimal sample complexity
Jun 25, 2026Haitong Liu, Deepak Narayanan Sridharan, David Steurer +1Optimal Sample Complexity Gaussian Mixture Models
ROMPAR: Morphological Completion and Demographic Unlearning for Romanian-Accented Speech Recognition
Jun 14, 2026Andrei-Marius Avram, Aureliu-Valentin Antonie, Ştefan-Bogdan Badea +3Automatic Speech Recognition Corpus
Adaptive Nucleus Truncation for Long-Form Reasoning
Jun 12, 2026Ousmane Amadou DiaLLM Reasoning Methods Truncation
Information-Theoretic Lower Bounds for Bit-Constrained Stochastic Optimization via a Reduction to Compressed Gaussian Mean Estimation
May 30, 2026Munsik KimInformation-Theoretic Limits Stochastic Optimization
Symmetric Hermite quadrature-based balanced truncation for learning linear dynamical systems from derivative data
May 29, 2026Sean Reiter, Steffen W. R. WernerReduced-Order Models Truncation
Shortcuts in the Tail: Debiasing via Post-Hoc Spectral Compression of Fine-Tuning Updates
May 29, 2026Edward Sun, Dmitrii TroitskiiFinetuning Shortcuts
Polynomial Context-Truncation Sensitivity in Autoregressive Language Models: Sequential Wyner-Ziv Bounds for KV Cache Compression
May 24, 2026Munsik KimKey-Value Cache Compression Rate-Distortion Theory
MinerU-Popo: Universal Post-Processing Model for Structured Document Parsing
May 24, 2026Bangrui Xu, Ziyang Miao, Xuanhe Zhou +8End-To-End Document Parsing Document Parsing
The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation
May 21, 2026Yifan Lan, Yuanpu Cao, Hanyu Wang +2Black Box Truncation
Three Costs of Amortizing Gaussian Process Inference with Neural Processes
May 20, 2026Robin YoungGaussian Process Covariance Estimation
EntmaxKV: Support-Aware Decoding for Entmax Attention
May 20, 2026Gonçalo Duarte, Miguel Couceiro, Marcos V. TrevisoEfficient Long-Context Inference Dynamic Sparse Attention
Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise
May 20, 2026Shubhada Agrawal, Siva Theja Maguluri, Martin ZubeldiaStochastic Approximation Concentration Inequalities
Decomposing MXFP4 quantization error for LLM reinforcement learning: reducible bias, recoverable deadzone, and an irreducible floor
May 19, 2026Xiaocan Li, Shiliang Wu, Zheng ShenLarge Language Model Quantization Low-Precision Training
To MRL or not to MRL: Text Embeddings are Robust to Truncation Without Matryoshka Learning, Except In Heavy Truncation Scenarios
May 15, 2026Sotaro Takeshita, Yurina Takeshita, Simone Paolo Ponzetto +1Matryoshka Representation Learning Patient-Specific Textual Embeddings
TruncProof: A Guardrail for LLM-based JSON Generation under Token-Length Constraints
May 13, 2026Yoshio Kato, Shuhei TarashimaLarge Language Model Generation Truncation
Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting
May 5, 2026Xiao Zhang, Yafei Li, Ruixiang Wang +3Neural Ordinary Differential Equations Ordinary Differential Equations
Mean Testing under Truncation beyond Gaussian
May 2, 2026Yuhao Wang, Roberto Imbuzeiro Oliveira, Themis GouleakisTruncation Regularity
The Truncation Blind Spot: How Decoding Strategies Systematically Exclude Human-Like Token Choices
Mar 19, 2026Esteban Garces Arias, Nurzhan Sapargali, Christian Heumann +1Truncation Constrained Decoding Strategies
Distilling the Essence: Efficient Reasoning Distillation via Sequence Truncation
Dec 24, 2025Wei-Rui Chen, Vignesh Kothapalli, Ata Fatahibaarzi +5Large Reasoning Models Recursive Reasoner

Sep 9, 2026 · stat.MLJ/K move · Enter open · S save

Why Learning Rediscovers the Closed-Form Diagonal Regularizer

Jeahn Han, Pyojin Kim

We identify a diagonal saturation principle in modal inverse problems: when truncation noise is isotropic, the Bayes-optimal Tikhonov shape is a closed-form power law Gamma_k proportional to lambda_k^|s| set by the prior alone, independent of the domain. Berry's random-wave conjecture decorrelates the truncation noise across modes, and Weyl's eigenvalue counting law supplies enough modes for the conclusion to survive empirical Berry violations. Together they predict an approximately flat loss landscape across the per-mode family, leaving narrow scope for a diagonal regularizer to robustly beat the closed form. On FEM-simulated acoustic rooms, the closed form is near-optimal relative to per-room oracle tuning across observation windows, and three diagonal architectures trained on the same data match its reconstruction error within 1 pp despite learning qualitatively different spectra. The framework extends to heat diffusion via a known exponential Green's function correction with no new free parameters. Saturation is restricted to the diagonal family: Learned Iterative Ridge crosses the boundary by exploiting cross-mode coupling, locating where learning starts to help.

Regularization Methods Ill-Posed Inverse Problem Truncation Saturation

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