Algorithmic Generalization

Latest papers

20 papers4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Assessing the Impact of Retrieval-Augmented Generation on Algorithmic Problem-Solving
Nov 6, 2026Gabriel Souza Baggio, Gabriel Machado Lunardi, Guilherme Medeiros Machado +3Retrieval-Augmented Code Generation LLM Code Generation
Federal University of Santa Maria, Roraima Avenue, 1000, Santa Maria, 97105-800, Rio Grande do Sul, Brazil · LyRIDS lab, ECE Engineering School, 10 Rue Sextius Michel, Paris, 75015, Île-de-France, France · Federal University of Rio Grande do Sul, Informatics Institute, Bento Gonçalves Avenue, 9500, Porto Alegre, 91501-970, Rio Grande do Sul, Brazil
Alignment via Generalization
Oct 25, 2026Shai Shalev-Shwartz, Amnon ShashuaAI Alignment PAC Learning
Algorithm Modelization: Transforming Optimization Algorithms into Evolvable Intelligence
Oct 16, 2026Jian Yao, Zhiyao Zhang, Yichen Li +2Learning to Optimize Algorithmic Generalization
Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Generalization Guarantees of Randomized Block Coordinate Descent for Nonconvex Learning
Oct 15, 2026Ruixi Hu, Liang WuAlgorithmic Generalization Generalization Bounds
Center of Statistical Research, School of Statistics and Data Science, Southwestern University of Finance and Economics, Chengdu, China
Certification-Enhanced Generalization Bounds
Oct 5, 2026Leo Elmecker-Plakolm, Matthew WickerAlgorithmic Stability Generalization Bounds
Department of Computing, Imperial College London, London, SW7 2AZ, UK
From Shortcut Learning to Discrete Neural Insertion Sort
Sep 25, 2026Konstantinos Mylonas, Thrasyvoulos SpyropoulosAlgorithmic Generalization Neural Algorithmic Reasoning
Emergent Models: Intelligence from Tiny Substrates
Aug 14, 2026Giacomo Bocchese, Nicola Giacobbo, Etienne Guichard +2Algorithmic Generalization
Wolfram Institute · Emergent Computing · Østfold University College
Grokking Is Conditional and Fragile: A Fully-Tractable, Multi-Seed Study at 12K Parameters
Jul 6, 2026Yoshiyuki OotaniPhase Transitions ML Reproducibility
Independent Researcher
Structure-Specific Representational Priors Causally Control the Grokking Delay
Jul 5, 2026Gunner Levi HoweTransformer Grokking
Radial Suppression Accelerates Algorithmic Generalization: A Geometric Analysis of Delayed Generalization
Jun 30, 2026Srijan Tiwari, Aditya Chauhan, Manjot SinghNeural Network Generalization Neural Representation Geometry
Indian Institute of Technology Roorkee
AlgoBench: Benchmarking Algorithmic Adaptation in Code Generation
Jun 30, 2026Xinyuan Song, Zekun Cai, Liang ZhaoSynthetic Benchmark Generation Code Generation Evaluation
Emory University, Atlanta, GA, USA · The University of Tokyo, Tokyo, Japan · LocationMind, Tokyo, Japan
BRo-JEPA: Learning Modular Arithmetic in Latent Space
May 31, 2026Divyansh Jha, Yuanfang Xie, Varan Mehra +1Zero-Shot Learning Joint-Embedding Predictive Architecture
1Georgia Institute of Technology · 2NYU Langone Health
Open Problem: Separating Geometric and Algorithmic Compression via Cayley-Table Completion
May 28, 2026Dongsung HuhStatistical Learning Theory Algorithmic Reasoning
Stochastic Gradient Descent with Momentum is Algorithmically Stable
May 27, 2026Yunwen Lei, Zimeng Wang, Xiaoming YuanMomentum Methods Algorithmic Stability
Department of Mathematics, The University of Hong Kong, Hong Kong, China · Department of Mathematics and Mathematical Statistics, Umeå University, Sweden
Slower Generalization, Faster Memorization: A Sweet Spot in Algorithmic Learning
May 14, 2026Shin So, Kyelim Lee, Albert NoNeural Network Generalization Neural Network Training Dynamics
Yonsei University
A Survey on Data-Dependent Worst-Case Generalization Bounds
May 13, 2026Hubert Leroux, Jean Marcus, Julien RogerNeural Network Generalization PAC-Bayesian Generalization Bounds
´Ecole polytechnique Palaiseau, France
On the Stability and Generalization of First-order Bilevel Minimax Optimization
Apr 22, 2026Xuelin Zhang, Peipei YuanMin-Max Optimization Bilevel Optimization
College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China · School of Artificial Intelligence, Jianghan University, Wuhan, 430056, China
Algorithmic Task Capture, Computational Complexity, and Inductive Bias of Infinite Transformers
Mar 11, 2026Orit Davidovich, Zohar RingelAlgorithmic Generalization Transformer
IBM Research, Haifa, Israel · Racah Institute of Physics, Hebrew University, Jerusalem, Israel
Intrinsic Task Symmetry Drives Generalization in Algorithmic Tasks
Mar 2, 2026Hyeonbin Hwang, Yeachan ParkNeural Network Generalization Grokking
KAIST · Sejong University
Generalization Bounds of Stochastic Gradient Descent in Homogeneous Neural Networks
Feb 26, 2026Wenquan Ma, Yang Sui, Jiaye Teng +3Generalization Bounds Algorithmic Generalization

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Assessing the Impact of Retrieval-Augmented Generation on Algorithmic Problem-Solving

Gabriel Souza Baggio, Gabriel Machado Lunardi, Guilherme Medeiros Machado, Subhankar Maity+2

Federal University of Santa Maria, Roraima Avenue, 1000, Santa Maria, 97105-800, Rio Grande do Sul, Brazil · LyRIDS lab, ECE Engineering School, 10 Rue Sextius Michel, Paris, 75015, Île-de-France, France · Federal University of Rio Grande do Sul, Informatics Institute, Bento Gonçalves Avenue, 9500, Porto Alegre, 91501-970, Rio Grande do Sul, Brazil

Retrieval-Augmented Code Generation LLM Code Generation Competitive Programming Algorithmic Generalization

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Competitive programming problems pose distinctive challenges for Large Language Models, as they demand not only proficient code generation but also advanced algorithmic reasoning. This study presents a Retrieval-Augmented Generation approach specifically designed to enhance the capacity of Large Language Models to address such problems. Our approach integrates an embedding-based retrieval mechanism and a similarity search algorithm to identify analogous problems within a knowledge database, employing a dynamically adjusted threshold to mitigate retrieval noise. We conducted an evaluation using the CodeContests dataset, focusing on the test split problems that exhibit similarity to instances from the training split. The experimental framework considered three conditions: (i) problems provided solely with their original descriptions, (ii) problems supplemented with randomly selected examples from the training split, and (iii) problems augmented with similar examples retrieved through the proposed method. In addition, we incorporated a Min-K membership inference analysis to examine whether the generated code solutions were influenced by potential memorization of training data within the evaluated Large Language Models. This complementary perspective enables a deeper understanding of model behavior by distinguishing genuine generalization through retrieval from implicit recall of pretraining samples. Performance was assessed using both pass rates and the CodeForces Elo rating of the problems. The results provide empirical evidence that similarity-based retrieval substantially enhances Large Language Models performance in competitive programming scenarios, offering an scalable framework for improving code generation in algorithmic problem-solving contexts.