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Enhancing Differential Testing with LLMs for Testing Deep Learning Libraries

https://doi.org/10.1145/3735637
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-319-46493-0_38openalex-snapshot
Identity Mappings in Deep Residual Networks
inferredcites →https://doi.org/10.1007/s10664-023-10389-6openalex-snapshot
Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow
inferredcites →https://doi.org/10.1007/s11432-011-4368-7openalex-snapshot
Strategies for scalable symbolic execution-driven test generation for programs
inferredcites →https://doi.org/10.1016/j.infsof.2022.107004openalex-snapshot
A comprehensive empirical study on bug characteristics of deep learning frameworks
inferredcites →https://doi.org/10.1109/icc.2018.8422832openalex-snapshot
A Deep Learning Approach to IoT Authentication
inferredcites →https://doi.org/10.1109/iccv.2015.312openalex-snapshot
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving
inferredcites →https://doi.org/10.1109/icse.2019.00107openalex-snapshot
CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning Libraries
inferredcites →https://doi.org/10.1109/icse43902.2021.00037openalex-snapshot
Graph-Based Fuzz Testing for Deep Learning Inference Engines
inferredcites →https://doi.org/10.1109/icse43902.2021.00146openalex-snapshot
PyCG: Practical Call Graph Generation in Python
inferredcites →https://doi.org/10.1109/icse48619.2023.00105openalex-snapshot
Fuzzing Automatic Differentiation in Deep-Learning Libraries
inferredcites →https://doi.org/10.1109/tcomm.2018.2878025openalex-snapshot
Deep Learning for Signal Authentication and Security in Massive Internet-of-Things Systems
inferredcites →https://doi.org/10.1145/3213846.3213866openalex-snapshot
An empirical study on TensorFlow program bugs
inferredcites →https://doi.org/10.1145/3324884.3416571openalex-snapshot
Audee
inferredcites →https://doi.org/10.1145/3368089.3409761openalex-snapshot
Deep learning library testing via effective model generation
inferredcites →https://doi.org/10.1145/3395363.3397380openalex-snapshot
Discovering discrepancies in numerical libraries
inferredcites →https://doi.org/10.1145/3460319.3464843openalex-snapshot
Predoo: precision testing of deep learning operators
inferredcites →https://doi.org/10.1145/3510003.3510041openalex-snapshot
Free lunch for testing
inferredcites →https://doi.org/10.1145/3510003.3510092openalex-snapshot
Muffin
inferredcites →https://doi.org/10.1145/3510003.3510165openalex-snapshot
EAGLE
inferredcites →https://doi.org/10.1145/3533767.3534220openalex-snapshot
DocTer: documentation-guided fuzzing for testing deep learning API functions
inferredcites →https://doi.org/10.1145/3540250.3549085openalex-snapshot
Fuzzing deep-learning libraries via automated relational API inference
inferredcites →https://doi.org/10.1145/3583566openalex-snapshot
COMET: Coverage-guided Model Generation For Deep Learning Library Testing
inferredcites →https://doi.org/10.1145/3587155openalex-snapshot
Toward Understanding Deep Learning Framework Bugs
inferredcites →https://doi.org/10.1145/3597503.3623343openalex-snapshot
Large Language Models are Edge-Case Generators: Crafting Unusual Programs for Fuzzing Deep Learning Libraries
inferredcites →https://doi.org/10.1145/3597926.3598067openalex-snapshot
Large Language Models Are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models
inferredcites →https://doi.org/10.1145/3597926.3598088openalex-snapshot
ACETest: Automated Constraint Extraction for Testing Deep Learning Operators
inferredcites →https://doi.org/10.1145/3628159openalex-snapshot
Generation-based Differential Fuzzing for Deep Learning Libraries
inferredcites →https://doi.org/10.1145/3649828openalex-snapshot
Enhancing Static Analysis for Practical Bug Detection: An LLM-Integrated Approach
inferredcites →https://doi.org/10.1145/3689736openalex-snapshot
WhiteFox: White-Box Compiler Fuzzing Empowered by Large Language Models
inferredcites →https://doi.org/10.2352/issn.2470-1173.2017.19.avm-023openalex-snapshot
Deep Reinforcement Learning framework for Autonomous Driving

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s10515-025-00588-4openalex-snapshot
Automated summarization of software documents: an LLM-based multi-agent approach
inferred← citeshttps://doi.org/10.1109/access.2026.3729738openalex-snapshot
LLM-Based Test Oracles: Source-of-Authority Taxonomy—A Systematic Literature Review
inferred← citeshttps://doi.org/10.1109/icst69053.2026.00023openalex-snapshot
How Effective Is Coverage-Guided Fuzzing to Test Deep Learning Library APIs?
inferred← citeshttps://doi.org/10.1109/trustcom66490.2025.00349openalex-snapshot
DeepLancet: Effectively Detecting Deep Learning Library Bugs via LLM-assisted Testcase Generation
inferred← citeshttps://doi.org/10.1109/tse.2026.3655712openalex-snapshot
Subgraph-Oriented Testing for Deep Learning Libraries
inferred← citeshttps://doi.org/10.1145/3808146openalex-snapshot
Automated Knowledge-Aware Test Reuse
inferred← citeshttps://doi.org/10.1145/3808162openalex-snapshot
LLM-Assisted Input-Requirement-Aware Differential Testing of Array Programming Frameworks
inferred← citeshttps://doi.org/10.1145/3808212openalex-snapshot
RAT: Retrieval-Augmented Testing of Certificate Revocation List Parsers in TLS Implementations
inferred← citeshttps://doi.org/10.1145/3832152openalex-snapshot
WASCII: Bridging WebAssembly Specifications and Implementations through LLM-Enhanced Validation
inferred← citeshttps://doi.org/10.1145/3837729.3840504openalex-snapshot
LPR+: Diverse Transformations for LLM-Aided Program Reduction
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