Preconditioner

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1 paper in the last four weeks, with none the four weeks before. 0.0% of all new papers.

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Improving Large Language Models for Code through Runtime Program-State Reasoning
Sep 28, 2026Hongwei Li, Spandan Garg, Yufan HuangSwe-Bench Verified Runtime
University of California, Santa Barbara · Microsoft
Knowing Is Not Enough: Information Retrievability as a Precondition to Effective LLM Oversight
Sep 2, 2026Xinyu Fu, Narayan Ramasubbu, Dennis GallettaLarge Language Models Fail Explainable AI Methods
Robinson College of Business Georgia State University 55 Park Place NE, Atlanta, GA 30303, USA · School of Business University of Pittsburgh 3950 Roberto and Vera Clemente Dr, Pittsburgh, PA 15260, USA
Graph Neural Multilevel Preconditioners for Iterative Solvers
Jul 30, 2026Zechen Zhang, Rui Peng Li, Yousef SaadAlgebraic Multigrid Spectral Preconditioning
University of Minnesota Minneapolis, MN, USA · CASA, Lawrence Livermore National Laboratory Livermore, CA, USA
Contraction-Gauge Preconditioning for Quantized Matrix Multiplication
Jul 21, 2026Piyush Sao, Narasinga Miniskar, Pedro Valero-Lara +2Matrix Multiplication Spectral Preconditioning
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA
PoLoRA: A Preconditioned Orthogonalized LoRA Optimizer
Jul 20, 2026Nikhil Ghosh, Tetiana Parshakova, Robert M. GowerMultimodal Continual Instruction Tuning Muon
Center for Computational Mathematics, Flatiron Institute, New York, NY
Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles
Jul 20, 2026Haichen Hu, David Simchi-LeviStochastic Convex Optimization Interval Regret
Center for Computational Science and Engineering, MIT · Department of Civil and Environmental Engineering, MIT · Institute for Data, Systems, and Society, MIT
A Precedent-Guided Co-Scientist for Side-Effect-Aware Drug Redesign
Jul 3, 2026Yujin Kim, Charmgil HongDrug Discovery Pharmacokinetics
Department of Computer Science and Electrical Engineering, Handong Global University, Pohang, Republic of Korea.
Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge
Jul 2, 2026Alex Brooker, Tim HughesAir Traffic Control Preconditioner
Airside Labs, London, United Kingdom · Mahino Research, Christchurch, New Zealand
Interface-Aware Neural Newton Preconditioning for Robust Cohesive Zone Model Simulations
Jun 30, 2026Zhangyong Liang, Huanhuan GaoFinite Element Method Spectral Preconditioning
National Center for Applied Mathematics, Tianjin University, Tianjin, 300072, China · School of Mechanical and Aerospace Engineering, Jilin University, Renmin Street 5988, 130025, Changchun, China
FiRe: Frequency Reparameterization as a Preconditioner for Periodic Implicit Neural Representations
Jun 28, 2026Harinandan Shukla, Rajarshi Verma, Jitin SinglaNeural Representations Reparameterization
Department of Computer Science and Engineering, IIT Roorkee · Department of Biosciences and Bioengineering, IIT Roorkee
Motor Angular Speed Preintegration for Multirotor UAV State Estimation
Jun 18, 2026Matěj Petrlík, Filip Novák, Robert Pěnička +1Inertial Navigation Systems State Estimation
Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
Pre-AF 13: An Interpretable Atrial Fibrillation Risk Score Mined from Discharge Reports
Jun 9, 2026Olga Shakhmatova, Dmitrii Kriukov, Daniil Larionov +10Cardiovascular Risk Prediction Cardiac
National Medical Research Center of Cardiology named after Academician E.I. Chazov, Moscow, Russia · Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia · Artificial Intelligence Research Institute (AIRI), Moscow, Russia +8
Neural Legendre-Fenchel transform with Hessian Preconditioning
Jun 8, 2026Basile Plus-Gourdon, Frank NielsenSpectral Preconditioning Hessian
´Ecole Normale Sup´erieure · Paris-Saclay, France · Sony Computer Science Laboratories Inc. +1
Contract2Tool: Learning Preconditions and Effects for Reliable Tool-Augmented LLM Agents
Jun 5, 2026Rahul Suresh Babu, Laxmipriya Ganesh IyerContracts Large Language Model Agents
Independent Researcher United States of America
PC Layer: Polynomial Weight Preconditioning for Improving LLM Pre-Training
Jun 4, 2026Senmiao Wang, Tiantian Fang, Haoran Zhang +4Large Language Model Pretraining Spectral Preconditioning
The Chinese University of Hong Kong, Shenzhen, China · Google LLC, Mountain View, CA, United States · Shenzhen International Center for Industrial and Applied Mathematics, Shenzhen2026 Research Institute of Big Data +1
Caught in the Act(ivation): Toward Pre-Output and Multi-Turn Detection of Credential Exfiltration by LLM Agents
Jun 2, 2026Kargi Chauhan, Pratibha RevankarIndirect Prompt Injection Attacker Large Language Model
University of California, Santa Cruz.
IMU Propagation as Preintegration
May 27, 2026Jianzhu HuaiInertial Measurement Units Inertial Navigation Systems
State Key Lab of Info Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei China
Reparametrizing Shampoo and SOAP for Subspace Basis Updates and BFloat16 Storage
May 25, 2026Alan Milligan, Zikun Xu, Simon Lacoste-Julien +2Matched Fp16 Intermediate Subspace
Mila & Université de Montréal · Microsoft · Concordia University & Mila +1
Navigating Potholes with Geometry-Aware Sharpness Minimization
May 15, 2026Simon Dufort-Labbé, Mehrab Hamidi, Razvan Pascanu +3Sharpness-Aware Minimization Flat Minima
Mila, Université de Montréal · Samsung – SAIL Montreal
Galilean State Estimation for Inertial Navigation Systems with Unknown Time Delay
May 13, 2026Giulio Delama, Martin Scheiber, Yixiao Ge +3Inertial Navigation Systems Extended Kalman Filter
Control of Networked Systems Group University of Klagenfurt 9020 Klagenfurt, Austria · Systems Theory and Robotics Group Australian National University ACT, 2601, Australia · I3S, CNRS, Universit´e Cˆote d’Azur and Institut Universitaire de France 06900 Sophia Antipolis, France
PREPING: Building Agent Memory without Tasks
May 11, 2026Yumin Choi, Sangwoo Park, Minki Kang +2Semantic Memory Preconditioner
KAIST
SGD for Variational Inference: Tackling Unbounded Variance via Preconditioning and Dynamic Batching
May 8, 2026Hippolyte Labarrière, Cesare Molinari, Silvia Villa +1Variational Inference Stochastic Gradient Descent
MaLGa, DIBRIS Università degli Studi di Genova Genoa, Italy · MaLGa, DIMA Università degli Studi di Genova Genoa, Italy · MaLGa, DIBRIS, IIT Università degli Studi di Genova Genoa, Italy
An Undecidability Proof for the Plan Existence Problem
Apr 24, 2026Antonis AchilleosLogic Tractability
Department of Computer Science, Reykjavik University, Iceland
Turbo-Muon: Almost-Orthogonal Pre-Conditioning for Fast Muon Updates
Dec 4, 2025Thibaut Boissin, Thomas Massena, Franck Mamalet +1Muon Spectral Preconditioning
IRIT-MISFIT · Institut de Recherche Technologique Saint-Exupery, France · DTIPG - SNCF, IRIT-MISFIT +2
What Is The Political Content in LLMs' Pre- and Post-Training Data?
Sep 26, 2025Tanise Ceron, Dmitry Nikolaev, Dominik Stammbach +1Large Language Model Bias Political Discourse
Bocconi University, Italy · University of Manchester, UK · Princeton University, USA

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Improving Large Language Models for Code through Runtime Program-State Reasoning

Hongwei Li, Spandan Garg, Yufan Huang

University of California, Santa Barbara · Microsoft

Swe-Bench Verified Runtime Post-Training Preconditioner

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Large language models receive limited explicit training in reasoning about runtime program states. We study whether training models to reason about runtime program states improves downstream software-engineering capabilities. We introduce two complementary program-state reasoning tasks. Buggy input-output reasoning requires a model to generate a concrete input that exposes a behavioral difference between a buggy program and a hidden correct implementation and to predict the resulting execution behavior. Precondition-postcondition reasoning requires an agent to symbolically characterize a bug-triggering precondition, predict the expected postcondition, explain their causal connection, and instantiate this reasoning as an executable regression test. By incorporating these two tasks into a staged post-training pipeline, we develop Comet-9B, a 9B language model based on Qwen3.5-9B Base. We evaluate the resulting checkpoints on repository-level patch generation, regression-test generation, and security PoC generation. Adding both program-state reasoning tasks to supervised fine-tuning (SFT) on issue resolution improves success rates by 7.25 percentage points on SWE-bench Pro and 9.70 points on SWT-Bench Verified. Sequential reinforcement learning on the two tasks yields further gains of 7.25, 26.79, and 4.67 percentage points on SWE-bench Pro, SWT-Bench Verified, and CyberGym, respectively. Despite having only 9B parameters, Comet-9B achieves a score comparable to the reported GPT-5.2 result on SWE-bench Pro and matches the reported success rate of a GPT-4o-based agent on SWT-Bench Verified.

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