:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zheng, Chengqi, Hu, Keya, Liu, Shuzhi, Wu, Tao, Ellis, Kevin, Pu, Yewen
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2605.21515
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Generating Pragmatic Examples to Train Neural Program Synthesizers
by: Vaduguru, Saujas, et al.
Published: (2023)

Is Programming by Example solved by LLMs?
by: Li, Wen-Ding, et al.
Published: (2024)

Bongards at the Boundary of Perception and Reasoning: Programs or Language?
by: Langenfeld, Cassidy, et al.
Published: (2026)

Combining Induction and Transduction for Abstract Reasoning
by: Li, Wen-Ding, et al.
Published: (2024)

When Robots Should Say "I Don't Know": Benchmarking Abstention in Embodied Question Answering
by: Wu, Tao, et al.
Published: (2025)

Read and Reap the Rewards: Learning to Play Atari with the Help of Instruction Manuals
by: Wu, Yue, et al.
Published: (2023)

Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
by: Schnabel, Tobias, et al.
Published: (2024)

Hypothesis Search: Inductive Reasoning with Language Models
by: Wang, Ruocheng, et al.
Published: (2023)

Prism: Symbolic Superoptimization of Tensor Programs
by: Wu, Mengdi, et al.
Published: (2026)

Can Prompt Difficulty be Online Predicted for Accelerating RL Finetuning of Reasoning Models?
by: Qu, Yun, et al.
Published: (2025)

AISSISTANT: Human-AI Collaborative Review and Perspective Research Workflows in Data Science
by: Gaddipati, Sasi Kiran, et al.
Published: (2025)

Joint Learning of Hierarchical Neural Options and Abstract World Model
by: Piriyakulkij, Wasu Top, et al.
Published: (2026)

How Do Transformers Learn Variable Binding in Symbolic Programs?
by: Wu, Yiwei, et al.
Published: (2025)

Explainable Diagnosis Prediction through Neuro-Symbolic Integration
by: Lu, Qiuhao, et al.
Published: (2024)

CAP: Controllable Alignment Prompting for Unlearning in LLMs
by: Wang, Zhaokun, et al.
Published: (2026)

A Comparison of Recent Algorithms for Symbolic Regression to Genetic Programming
by: Radwan, Yousef A., et al.
Published: (2024)

PruneSymNet: A Symbolic Neural Network and Pruning Algorithm for Symbolic Regression
by: Wu, Min, et al.
Published: (2024)

Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale
by: Zhou, Fan, et al.
Published: (2024)

Program Machine Policy: Addressing Long-Horizon Tasks by Integrating Program Synthesis and State Machines
by: Lin, Yu-An, et al.
Published: (2023)

A New Type of Adversarial Examples
by: Nie, Xingyang, et al.
Published: (2025)

Bayesian-Symbolic Integration for Uncertainty-Aware Parking Prediction
by: Nezhadettehad, Alireza, et al.
Published: (2026)

Decompose, Structure, and Repair: A Neuro-Symbolic Framework for Autoformalization via Operator Trees
by: Liu, Xiaoyang, et al.
Published: (2026)

Comprehension Without Competence: Architectural Limits of LLMs in Symbolic Computation and Reasoning
by: Zhang, Zheng
Published: (2025)

Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)

GREATERPROMPT: A Unified, Customizable, and High-Performing Open-Source Toolkit for Prompt Optimization
by: Zheng, Wenliang, et al.
Published: (2025)

Neural-Symbolic Message Passing with Dynamic Pruning
by: Zhang, Chongzhi, et al.
Published: (2025)

Operator Feature Neural Network for Symbolic Regression
by: Deng, Yusong, et al.
Published: (2024)

Active Preference Inference using Language Models and Probabilistic Reasoning
by: Piriyakulkij, Wasu Top, et al.
Published: (2023)

Programmatic Video Prediction Using Large Language Models
by: Tang, Hao, et al.
Published: (2025)

Principle-Evolvable Scientific Discovery via Uncertainty Minimization
by: Pu, Yingming, et al.
Published: (2026)

PiFlow: Principle-Aware Scientific Discovery with Multi-Agent Collaboration
by: Pu, Yingming, et al.
Published: (2025)

Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation
by: Wu, Wenyuan, et al.
Published: (2025)

Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
by: Cook, Jonathan, et al.
Published: (2025)

Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
by: Cho, Yeseul, et al.
Published: (2025)

Prompt Tuning with Diffusion for Few-Shot Pre-trained Policy Generalization
by: Hu, Shengchao, et al.
Published: (2024)

Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
by: Tao, Lue, et al.
Published: (2023)

Symbolic Foundation Regressor on Complex Networks
by: Liu, Weiting, et al.
Published: (2025)

Adversarial Examples in the Physical World: A Survey
by: Wang, Jiakai, et al.
Published: (2023)

VisualPredicator: Learning Abstract World Models with Neuro-Symbolic Predicates for Robot Planning
by: Liang, Yichao, et al.
Published: (2024)

Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation
by: Dhar, Soumyadeep, et al.
Published: (2025)