On the public citation graph
LLM for Mobile: An Initial Roadmap
0 signed · 142 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-030-01237-3_12openalex-snapshot
A Systematic DNN Weight Pruning Framework Using Alternating Direction Method of Multipliers
inferredcites →https://doi.org/10.1007/978-3-030-58536-5_5openalex-snapshot
Post-training Piecewise Linear Quantization for Deep Neural Networks
inferredcites →https://doi.org/10.1007/978-3-031-49601-1_6openalex-snapshot
Context-Enhanced Language Models for Generating Multi-paper Citations
inferredcites →https://doi.org/10.1007/978-3-642-30921-2_10openalex-snapshot
Trustworthy Execution on Mobile Devices: What Security Properties Can My Mobile Platform Give Me?
inferredcites →https://doi.org/10.1007/s10664-019-09764-zopenalex-snapshot
CDA: Characterising Deprecated Android APIs
inferredcites →https://doi.org/10.1007/s10664-023-10362-3openalex-snapshot
What is an app store? The software engineering perspective
inferredcites →https://doi.org/10.1007/s11023-020-09548-1openalex-snapshot
GPT-3: Its Nature, Scope, Limits, and Consequences
inferredcites →https://doi.org/10.1016/j.infsof.2017.04.001openalex-snapshot
Static analysis of android apps: A systematic literature review
inferredcites →https://doi.org/10.1016/j.infsof.2021.106566openalex-snapshot
Augmenting commit classification by using fine-grained source code changes and a pre-trained deep neural language model
inferredcites →https://doi.org/10.1016/j.ins.2020.02.037openalex-snapshot
A training-integrity privacy-preserving federated learning scheme with trusted execution environment
inferredcites →https://doi.org/10.1038/s42256-023-00626-4openalex-snapshot
Parameter-efficient fine-tuning of large-scale pre-trained language models
inferredcites →https://doi.org/10.1109/ase51524.2021openalex-snapshot
2021 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)
inferredcites →https://doi.org/10.1109/ase56229.2023.00089openalex-snapshot
Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting
inferredcites →https://doi.org/10.1109/ase56229.2023.00148openalex-snapshot
Towards Autonomous Testing Agents via Conversational Large Language Models
inferredcites →https://doi.org/10.1109/cspa60979.2024.10525270openalex-snapshot
IRAG: Iterative Retrieval Augmented Generation for SLU
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00031openalex-snapshot
DaST: Data-Free Substitute Training for Adversarial Attacks
inferredcites →https://doi.org/10.1109/cvpr42600.2020.00807openalex-snapshot
Low-Rank Compression of Neural Nets: Learning the Rank of Each Layer
inferredcites →https://doi.org/10.1109/cvpr42600.2020.01321openalex-snapshot
TBT: Targeted Neural Network Attack With Bit Trojan
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01466openalex-snapshot
Investigating Top-k White-Box and Transferable Black-box Attack
inferredcites →https://doi.org/10.1109/cvpr52729.2023.00392openalex-snapshot
TrojViT: Trojan Insertion in Vision Transformers
inferredcites →https://doi.org/10.1109/cvpr52729.2023.01544openalex-snapshot
DepGraph: Towards Any Structural Pruning
inferredcites →https://doi.org/10.1109/dac18074.2021.9586199openalex-snapshot
SEALing Neural Network Models in Encrypted Deep Learning Accelerators
inferredcites →https://doi.org/10.1109/dsn48063.2020.00031openalex-snapshot
Leaky DNN: Stealing Deep-Learning Model Secret with GPU Context-Switching Side-Channel
inferredcites →https://doi.org/10.1109/eurospw59978.2023.00016openalex-snapshot
ATLAS: Automatically Detecting Discrepancies Between Privacy Policies and Privacy Labels
inferredcites →https://doi.org/10.1109/host45689.2020.9300274openalex-snapshot
DeepEM: Deep Neural Networks Model Recovery through EM Side-Channel Information Leakage
inferredcites →https://doi.org/10.1109/iccv.2019.00145openalex-snapshot
Similarity-Preserving Knowledge Distillation
inferredcites →https://doi.org/10.1109/icse-fose59343.2023.00008openalex-snapshot
Large Language Models for Software Engineering: Survey and Open Problems
inferredcites →https://doi.org/10.1109/icse.2015.48openalex-snapshot
IccTA: Detecting Inter-Component Privacy Leaks in Android Apps
inferredcites →https://doi.org/10.1109/icse48619.2023.00119openalex-snapshot
Fill in the Blank: Context-aware Automated Text Input Generation for Mobile GUI Testing
inferredcites →https://doi.org/10.1109/icse48619.2023.00194openalex-snapshot
Large Language Models are Few-shot Testers: Exploring LLM-based General Bug Reproduction
inferredcites →https://doi.org/10.1109/icsme55016.2022.00020openalex-snapshot
Evaluation of Context-Aware Language Models and Experts for Effort Estimation of Software Maintenance Issues
inferredcites →https://doi.org/10.1109/icsme55016.2022.00080openalex-snapshot
Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection
inferredcites →https://doi.org/10.1109/ipdps54959.2023.00042openalex-snapshot
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
inferredcites →https://doi.org/10.1109/issre59848.2023.00026openalex-snapshot
LLaMA-Reviewer: Advancing Code Review Automation with Large Language Models through Parameter-Efficient Fine-Tuning
inferredcites →https://doi.org/10.1109/msr.2019.00065openalex-snapshot
Negative Results on Mining Crypto-API Usage Rules in Android Apps
inferredcites →https://doi.org/10.1109/re48521.2020.00029openalex-snapshot
A Deep Context-wise Method for Coreference Detection in Natural Language Requirements
inferredcites →https://doi.org/10.1109/saner53432.2022.00054openalex-snapshot
Aspect-Based API Review Classification: How Far Can Pre-Trained Transformer Model Go?
inferredcites →https://doi.org/10.1109/saner56733.2023.00049openalex-snapshot
A Multi-Step Learning Approach to Assist Code Review
inferredcites →https://doi.org/10.1109/sc41405.2020.00073openalex-snapshot
BATCH: Machine Learning Inference Serving on Serverless Platforms with Adaptive Batching
inferredcites →https://doi.org/10.1109/snams60348.2023.10375400openalex-snapshot
Semantic Compression with Large Language Models
inferredcites →https://doi.org/10.1109/sp.2019.00065openalex-snapshot
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
inferredcites →https://doi.org/10.1109/sp46214.2022.9833743openalex-snapshot
DeepSteal: Advanced Model Extractions Leveraging Efficient Weight Stealing in Memories
inferredcites →https://doi.org/10.1109/tai.2021.3133824openalex-snapshot
Intellectual Property Protection for Deep Learning Models: Taxonomy, Methods, Attacks, and Evaluations
inferredcites →https://doi.org/10.1109/tcsii.2020.2973007openalex-snapshot
Open DNN Box by Power Side-Channel Attack
inferredcites →https://doi.org/10.1109/tdsc.2019.2908939openalex-snapshot
Dating with Scambots: Understanding the Ecosystem of Fraudulent Dating Applications
inferredcites →https://doi.org/10.1109/tifs.2017.2656460openalex-snapshot
Understanding Android App Piggybacking: A Systematic Study of Malicious Code Grafting
inferredcites →https://doi.org/10.1109/tifs.2021.3106169openalex-snapshot
Stealing Neural Network Structure Through Remote FPGA Side-Channel Analysis
inferredcites →https://doi.org/10.1109/tifs.2022.3172213openalex-snapshot
Smart App Attack: Hacking Deep Learning Models in Android Apps
inferredcites →https://doi.org/10.1109/tpami.2024.3367329openalex-snapshot
A Comprehensive Survey of Continual Learning: Theory, Method and Application
inferredcites →https://doi.org/10.1109/tpds.2020.3030548openalex-snapshot
The Deep Learning Compiler: A Comprehensive Survey
inferredcites →https://doi.org/10.1109/tr.2018.2865733openalex-snapshot
Automated Testing of Android Apps: A Systematic Literature Review
inferredcites →https://doi.org/10.1109/trustcom.2015.357openalex-snapshot
Trusted Execution Environment: What It is, and What It is Not
inferredcites →https://doi.org/10.1109/tse.2014.2360674openalex-snapshot
Investigating Country Differences in Mobile App User Behavior and Challenges for Software Engineering
inferredcites →https://doi.org/10.1109/tse.2019.2901679openalex-snapshot
Rebooting Research on Detecting Repackaged Android Apps: Literature Review and Benchmark
inferredcites →https://doi.org/10.1109/tse.2021.3114381openalex-snapshot
Research on Third-Party Libraries in Android Apps: A Taxonomy and Systematic Literature Review
inferredcites →https://doi.org/10.1109/tse.2022.3227559openalex-snapshot
BEQAIN: An Effective and Efficient Identifier Normalization Approach With BERT and the Question Answering System
inferredcites →https://doi.org/10.1109/tse.2024.3368208openalex-snapshot
Software Testing With Large Language Models: Survey, Landscape, and Vision
inferredcites →https://doi.org/10.1109/wacv57701.2024.00097openalex-snapshot
TSP-Transformer: Task-Specific Prompts Boosted Transformer for Holistic Scene Understanding
inferredcites →https://doi.org/10.1145/268946.268962openalex-snapshot
Manufacturing cheap, resilient, and stealthy opaque constructs
inferredcites →https://doi.org/10.1145/2810103openalex-snapshot
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security
inferredcites →https://doi.org/10.1145/2810103.2813687openalex-snapshot
Privacy-Preserving Deep Learning
inferredcites →https://doi.org/10.1145/2886012openalex-snapshot
Protecting Software through Obfuscation
inferredcites →https://doi.org/10.1145/2931037.2931044openalex-snapshot
DroidRA: taming reflection to support whole-program analysis of Android apps
inferredcites →https://doi.org/10.1145/3005348openalex-snapshot
Structured Pruning of Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/3196398.3196412openalex-snapshot
Why are Android apps removed from Google Play?
inferredcites →https://doi.org/10.1145/3196494.3196550openalex-snapshot
Protecting Intellectual Property of Deep Neural Networks with Watermarking
inferredcites →https://doi.org/10.1145/3213846.3213857openalex-snapshot
CiD: automating the detection of API-related compatibility issues in Android apps
inferredcites →https://doi.org/10.1145/3238147.3238191openalex-snapshot
API method recommendation without worrying about the task-API knowledge gap
inferredcites →https://doi.org/10.1145/3293882.3330564openalex-snapshot
A large-scale study of application incompatibilities in Android
inferredcites →https://doi.org/10.1145/3497776.3517770openalex-snapshot
MLIR-based code generation for GPU tensor cores
inferredcites →https://doi.org/10.1145/3510003.3510128openalex-snapshot
Towards automatically repairing compatibility issues in published Android apps
inferredcites →https://doi.org/10.1145/3510003.3510157openalex-snapshot
Automated handling of anaphoric ambiguity in requirements
inferredcites →https://doi.org/10.1145/3510003.3510160openalex-snapshot
On the importance of building high-quality training datasets for neural code search
inferredcites →https://doi.org/10.1145/3510003.3510621openalex-snapshot
Using pre-trained models to boost code review automation
inferredcites →https://doi.org/10.1145/3510003.3511561openalex-snapshot
Using deep learning to generate complete log statements
inferredcites →https://doi.org/10.1145/3528588.3528651openalex-snapshot
Identification of intra-domain ambiguity using transformer-based machine learning
inferredcites →https://doi.org/10.1145/3533767.3534390openalex-snapshot
An extensive study on pre-trained models for program understanding and generation
inferredcites →https://doi.org/10.1145/3540250.3549099openalex-snapshot
AUGER: automatically generating review comments with pre-training models
inferredcites →https://doi.org/10.1145/3544968openalex-snapshot
Deep Learning for Android Malware Defenses: A Systematic Literature Review
inferredcites →https://doi.org/10.1145/3551349.3556955openalex-snapshot
CoditT5: Pretraining for Source Code and Natural Language Editing
inferredcites →https://doi.org/10.1145/3551349.3561151openalex-snapshot
Mining Android API Usage to Generate Unit Test Cases for Pinpointing Compatibility Issues
inferredcites →https://doi.org/10.1145/3574158openalex-snapshot
Demystifying Hidden Sensitive Operations in Android Apps
inferredcites →https://doi.org/10.1145/3597503.3623298openalex-snapshot
CrashTranslator: Automatically Reproducing Mobile Application Crashes Directly from Stack Trace
inferredcites →https://doi.org/10.1145/3597503.3623306openalex-snapshot
Exploring the Potential of ChatGPT in Automated Code Refinement: An Empirical Study
inferredcites →https://doi.org/10.1145/3597503.3623342openalex-snapshot
Large Language Models for Test-Free Fault Localization
inferredcites →https://doi.org/10.1145/3597503.3639144openalex-snapshot
Investigating White-Box Attacks for On-Device Models
inferredcites →https://doi.org/10.1145/3597926openalex-snapshot
Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis
inferredcites →https://doi.org/10.1145/3597926.3598113openalex-snapshot
ModelObfuscator: Obfuscating Model Information to Protect Deployed ML-Based Systems
inferredcites →https://doi.org/10.1145/3600006.3613163openalex-snapshot
Paella: Low-latency Model Serving with Software-defined GPU Scheduling
inferredcites →https://doi.org/10.1145/3600006.3613165openalex-snapshot
Efficient Memory Management for Large Language Model Serving with PagedAttention
inferredcites →https://doi.org/10.1145/3638550.3641130openalex-snapshot
Penetrative AI: Making LLMs Comprehend the Physical World
inferredcites →https://doi.org/10.1145/3641540openalex-snapshot
On the Reliability and Explainability of Language Models for Program Generation
inferredcites →https://doi.org/10.1145/3643733openalex-snapshot
LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
inferredcites →https://doi.org/10.1145/3643916.3645030openalex-snapshot
Investigating the Efficacy of Large Language Models for Code Clone Detection
inferredcites →https://doi.org/10.1145/3649856openalex-snapshot
PP-CSA: Practical Privacy-Preserving Software Call Stack Analysis
inferredcites →https://doi.org/10.1145/3650212.3652119openalex-snapshot
Model-less Is the Best Model: Generating Pure Code Implementations to Replace On-Device DL Models
inferredcites →https://doi.org/10.1201/9781003162810-13openalex-snapshot
A Survey of Quantization Methods for Efficient Neural Network Inference
inferredcites →https://doi.org/10.14722/ndss.2023.24103openalex-snapshot
OBSan: An Out-Of-Bound Sanitizer to Harden DNN Executables
inferredcites →https://doi.org/10.18130/v32n5copenalex-snapshot
A Security Architecture for Survivability Mechanisms
inferredcites →https://doi.org/10.18653/v1/2020.acl-main.740openalex-snapshot
Don’t Stop Pretraining: Adapt Language Models to Domains and Tasks
inferredcites →https://doi.org/10.18653/v1/2020.findings-emnlp.372openalex-snapshot
TinyBERT: Distilling BERT for Natural Language Understanding
inferredcites →https://doi.org/10.18653/v1/2020.repl4nlp-1.18openalex-snapshot
Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning
inferredcites →https://doi.org/10.18653/v1/2021.acl-long.47openalex-snapshot
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.243openalex-snapshot
The Power of Scale for Parameter-Efficient Prompt Tuning
inferredcites →https://doi.org/10.18653/v1/2022.acl-long.358openalex-snapshot
Dynamic Prefix-Tuning for Generative Template-based Event Extraction
inferredcites →https://doi.org/10.18653/v1/2023.acl-demo.54openalex-snapshot
Petals: Collaborative Inference and Fine-tuning of Large Models
inferredcites →https://doi.org/10.18653/v1/2024.naacl-long.389openalex-snapshot
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
inferredcites →https://doi.org/10.18653/v1/d16-1139openalex-snapshot
Sequence-Level Knowledge Distillation
inferredcites →https://doi.org/10.18653/v1/d19-1441openalex-snapshot
Patient Knowledge Distillation for BERT Model Compression
inferredcites →https://doi.org/10.20533/jitst.2046.3723.2019.0077openalex-snapshot
A New User-Apps Interactions Dataset for Behavioral Profiling Using Smartphones
inferredcites →https://doi.org/10.21437/interspeech.2018-1417openalex-snapshot
Semi-Orthogonal Low-Rank Matrix Factorization for Deep Neural Networks
inferredcites →https://doi.org/10.2478/popets-2021-0011openalex-snapshot
Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning
inferredcites →https://doi.org/10.48550/arxiv.2101.03961openalex-snapshot
Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
inferredcites →https://doi.org/10.48550/arxiv.2201.11903openalex-snapshot
BNAI, NO-TOKEN, and MIND-UNITY: Pillars of a Systemic Revolution in Artificial Intelligence
inferredcites →https://doi.org/10.48550/arxiv.2204.02311openalex-snapshot
PaLM: Scaling Language Modeling with Pathways
inferredcites →https://doi.org/10.52202/068431-0142openalex-snapshot
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
inferredcites →https://doi.org/10.52202/075280-0540openalex-snapshot
Distributed Inference and Fine-tuning of Large Language Models Over The Internet
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-12993-2_20openalex-snapshot
Evaluating AI-Optimized Mobile Design: A Mixed-Method Study on Bootstrap Performance and ChatGPT Text Analysis for MSME Websites
inferred← citeshttps://doi.org/10.1007/978-3-032-23271-7_18openalex-snapshot
Enhancing Weak LLM Performance on Edge Devices Through Retrieval-Augmented Generation: A Benchmark Study
inferred← citeshttps://doi.org/10.1016/j.cosrev.2026.100916openalex-snapshot
LLM in the middle: A systematic review of threats and mitigations to real-world LLM-based systems
inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104546openalex-snapshot
Large language models for transportation research: Methodologies, state of the art, and future opportunities
inferred← citeshttps://doi.org/10.1109/cloud67622.2025.00058openalex-snapshot
Temporal Fusion Transformer Based Vertical Scaling Management for Kubernetes
inferred← citeshttps://doi.org/10.1109/cloud72782.2026.00016openalex-snapshot
BridgeScheduler: Non-Intrusive Sensing and Collaborative Scheduling for Hybrid Edge-Cloud Environments
inferred← citeshttps://doi.org/10.1109/hipc66333.2025.00026openalex-snapshot
CALL: Context-Aware Low-Latency Retrieval in Disk-Based Vector Databases
inferred← citeshttps://doi.org/10.1109/iccv51701.2025.01791openalex-snapshot
PixTalk: Controlling Photorealistic Image Processing and Editing with Language
inferred← citeshttps://doi.org/10.1109/netcrypt65877.2025.11102417openalex-snapshot
Mitigating Hallucinations in Small Language Models: A Performance Analysis of DoLa Optimization for Mobile Devices
inferred← citeshttps://doi.org/10.1109/tmc.2025.3642580openalex-snapshot
Recursive Offloading for LLM Serving in Multi-Tier Networks
inferred← citeshttps://doi.org/10.1145/3702977openalex-snapshot
Demystifying React Native Android Apps for Static Analysis
inferred← citeshttps://doi.org/10.1145/3770855.3818662openalex-snapshot
Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G
inferred← citeshttps://doi.org/10.1145/3807455openalex-snapshot
Foundation Models for Autonomous Driving Systems: An Initial Roadmap
inferred← citeshttps://doi.org/10.1145/3819579openalex-snapshot
Mobile App Analysis in the New Era: Challenges and the Road Ahead
inferred← citeshttps://doi.org/10.1145/3843770openalex-snapshot
BASFuzz: Toward Robustness Evaluation of LLM-based NLP Software via Automated Fuzz Testing
inferred← citeshttps://doi.org/10.3390/electronics15173865openalex-snapshot
MorphCloud-LLM: Elastic Spot-Instance-Aware LLM Serving with Transparent Preemption Recovery and Speculative Decoding Continuity
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.