{"list":"other","total":53,"rows":[{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"2407.21783","title":"The Llama 3 Herd of Models","created":"2024-07-31","cited_by_count":14715},{"id":"2107.03374","title":"Evaluating Large Language Models Trained on Code","created":"2021-07-07","cited_by_count":8320},{"id":"2309.06180","title":"Efficient Memory Management for Large Language Model Serving with PagedAttention","created":"2023-09-12","cited_by_count":5944},{"id":"2410.21276","title":"GPT-4o System Card","created":"2024-10-25","cited_by_count":4588},{"id":"2108.07732","title":"Program Synthesis with Large Language Models","created":"2021-08-16","cited_by_count":3637},{"id":"2309.16609","title":"Qwen Technical Report","created":"2023-09-28","cited_by_count":3344},{"id":"2403.05530","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","created":"2024-03-08","cited_by_count":3224},{"id":"2308.12950","title":"Code Llama: Open Foundation Models for Code","created":"2023-08-24","cited_by_count":2139},{"id":"2407.10671","title":"Qwen2 Technical Report","created":"2024-07-15","cited_by_count":2120},{"id":"2207.05221","title":"Language Models (Mostly) Know What They Know","created":"2022-07-11","cited_by_count":1856},{"id":"2305.01210","title":"Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation","created":"2023-05-02","cited_by_count":1391},{"id":"2002.08155","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","created":"2020-02-19","cited_by_count":1310},{"id":"2409.12186","title":"Qwen2.5-Coder Technical Report","created":"2024-09-18","cited_by_count":1203},{"id":"2401.14196","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","created":"2024-01-25","cited_by_count":1181},{"id":"2306.13063","title":"Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs","created":"2023-06-22","cited_by_count":974},{"id":"2211.09527","title":"Ignore Previous Prompt: Attack Techniques For Language Models","created":"2022-11-17","cited_by_count":832},{"id":"2102.04664","title":"CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation","created":"2021-02-09","cited_by_count":744},{"id":"1909.09436","title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search","created":"2019-09-20","cited_by_count":654},{"id":"2009.08366","title":"GraphCodeBERT: Pre-training Code Representations with Data Flow","created":"2020-09-17","cited_by_count":609},{"id":"2009.10297","title":"CodeBLEU: a Method for Automatic Evaluation of Code Synthesis","created":"2020-09-22","cited_by_count":479},{"id":"2211.11501","title":"DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation","created":"2022-11-18","cited_by_count":452},{"id":"2305.07922","title":"CodeT5+: Open Code Large Language Models for Code Understanding and Generation","created":"2023-05-13","cited_by_count":333},{"id":"1909.03496","title":"Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks","created":"2019-09-08","cited_by_count":272},{"id":"2410.05295","title":"AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs","created":"2024-10-03","cited_by_count":199},{"id":"2211.03622","title":"Do Users Write More Insecure Code with AI Assistants?","created":"2022-11-07","cited_by_count":192},{"id":"2403.18624","title":"Vulnerability Detection with Code Language Models: How Far Are We?","created":"2024-03-27","cited_by_count":139},{"id":"2212.10264","title":"ReCode: Robustness Evaluation of Code Generation Models","created":"2022-12-20","cited_by_count":103},{"id":"2405.17238","title":"IRIS: LLM-Assisted Static Analysis for Detecting Security Vulnerabilities","created":"2024-05-27","cited_by_count":103},{"id":"2312.12575","title":"LLMs Cannot Reliably Identify and Reason About Security Vulnerabilities (Yet?): A Comprehensive Evaluation, Framework, and Benchmarks","created":"2023-12-19","cited_by_count":97},{"id":"2201.08698","title":"Natural Attack for Pre-trained Models of Code","created":"2022-01-21","cited_by_count":75},{"id":"2002.08653","title":"Detecting Code Clones with Graph Neural Networkand Flow-Augmented Abstract Syntax Tree","created":"2020-02-20","cited_by_count":69},{"id":"1910.07517","title":"Adversarial Examples for Models of Code","created":"2019-10-15","cited_by_count":63},{"id":"2103.01498","title":"A Survey On Universal Adversarial Attack","created":"2021-03-02","cited_by_count":59},{"id":"2501.08200","title":"CWEval: Outcome-driven Evaluation on Functionality and Security of LLM Code Generation","created":"2025-01-14","cited_by_count":59},{"id":"2206.00052","title":"CodeAttack: Code-Based Adversarial Attacks for Pre-trained Programming Language Models","created":"2022-05-31","cited_by_count":53},{"id":"2002.03043","title":"Semantic Robustness of Models of Source Code","created":"2020-02-07","cited_by_count":45},{"id":"2008.01566","title":"On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations","created":"2020-07-31","cited_by_count":44},{"id":"2408.16498","title":"A Survey on Evaluating Large Language Models in Code Generation Tasks","created":"2024-08-29","cited_by_count":44},{"id":"2002.04694","title":"Adversarial Robustness for Code","created":"2020-02-11","cited_by_count":38},{"id":"2406.06025","title":"RepoQA: Evaluating Long Context Code Understanding","created":"2024-06-10","cited_by_count":35},{"id":"2312.04730","title":"DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions","created":"2023-12-07","cited_by_count":33},{"id":"2103.11882","title":"Generating Adversarial Computer Programs using Optimized Obfuscations","created":"2021-03-18","cited_by_count":22},{"id":"2108.00213","title":"Adversarial Robustness of Deep Code Comment Generation","created":"2021-07-31","cited_by_count":22},{"id":"2402.19475","title":"The Counterfeit Conundrum: Can Code Language Models Grasp the Nuances of Their Incorrect Generations?","created":"2024-02-29","cited_by_count":20},{"id":"1703.06857","title":"On the Limitation of Convolutional Neural Networks in Recognizing Negative Images","created":"2017-03-20","cited_by_count":17},{"id":"2202.05982","title":"Detecting False Alarms from Automatic Static Analysis Tools: How Far are We?","created":"2022-02-12","cited_by_count":17},{"id":"2202.06043","title":"RoPGen: Towards Robust Code Authorship Attribution via Automatic Coding Style Transformation","created":"2022-02-12","cited_by_count":15},{"id":"2408.02509","title":"Black-Box Adversarial Attacks on LLM-Based Code Completion","created":"2024-08-05","cited_by_count":14},{"id":"2301.02412","title":"Code Difference Guided Adversarial Example Generation for Deep Code Models","created":"2023-01-06","cited_by_count":9},{"id":"2311.07553","title":"An Extensive Study on Adversarial Attack against Pre-trained Models of Code","created":"2023-11-13","cited_by_count":8},{"id":"2305.05896","title":"A Black-Box Attack on Code Models via Representation Nearest Neighbor Search","created":"2023-05-10","cited_by_count":3},{"id":"2502.05150","title":"CodeSCM: Causal Analysis for Multi-Modal Code Generation","created":"2025-02-07","cited_by_count":2}],"next_cursor":null}