ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries

Αποθηκεύτηκε σε:
Λεπτομέρειες βιβλιογραφικής εγγραφής
Εκδόθηκε σε:arXiv.org (Dec 18, 2024), p. n/a
Κύριος συγγραφέας: Maharaj, Kishan
Άλλοι συγγραφείς: Munigala, Vitobha, Tamilselvam, Srikanth G, Kumar, Prince, Sen, Sayandeep, Kodeswaran, Palani, Mishra, Abhijit, Bhattacharyya, Pushpak
Έκδοση:
Cornell University Library, arXiv.org
Θέματα:
Διαθέσιμο Online:Citation/Abstract
Full text outside of ProQuest
Ετικέτες: Προσθήκη ετικέτας
Δεν υπάρχουν, Καταχωρήστε ετικέτα πρώτοι!

MARC

LEADER 00000nab a2200000uu 4500
001 3119817256
003 UK-CbPIL
022 |a 2331-8422 
035 |a 3119817256 
045 0 |b d20241218 
100 1 |a Maharaj, Kishan 
245 1 |a ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries 
260 |b Cornell University Library, arXiv.org  |c Dec 18, 2024 
513 |a Working Paper 
520 3 |a Recent advancements in large language models (LLMs) have significantly enhanced their ability to understand both natural language and code, driving their use in tasks like natural language-to-code (NL2Code) and code summarization. However, LLMs are prone to hallucination-outputs that stray from intended meanings. Detecting hallucinations in code summarization is especially difficult due to the complex interplay between programming and natural languages. We introduce a first-of-its-kind dataset with \(\sim\)10K samples, curated specifically for hallucination detection in code summarization. We further propose a novel Entity Tracing Framework (ETF) that a) utilizes static program analysis to identify code entities from the program and b) uses LLMs to map and verify these entities and their intents within generated code summaries. Our experimental analysis demonstrates the effectiveness of the framework, leading to a 0.73 F1 score. This approach provides an interpretable method for detecting hallucinations by grounding entities, allowing us to evaluate summary accuracy. 
653 |a Program verification (computers) 
653 |a Large language models 
653 |a Summaries 
653 |a Tracing 
653 |a Task complexity 
700 1 |a Munigala, Vitobha 
700 1 |a Tamilselvam, Srikanth G 
700 1 |a Kumar, Prince 
700 1 |a Sen, Sayandeep 
700 1 |a Kodeswaran, Palani 
700 1 |a Mishra, Abhijit 
700 1 |a Bhattacharyya, Pushpak 
773 0 |t arXiv.org  |g (Dec 18, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3119817256/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2410.14748