Multi-task LLMs for Bug Classification: Efficient Inference with Auxiliary Decoding Heads
The rapid adoption of LLM-powered code generation has dramatically accelerated software development, yet effective verification methods remain severely underdeveloped. Existing bug localization techniques are either prohibitively expensive, requiring minutes of agentic reasoning and thousands of generated tokens per file, and/or operate at coarse function-level granularity unsuitable for precise debugging. While works that focus on line-level granularity and are more light-weight are often limited in their performance or context size. We introduce a novel line-level bug localization approach that addresses these limitations through three key contributions: (1) a token alignment algorithm ...
| Authors | Nikolai Rozanov |
|---|---|
| Primary category | cs.SE |
| Published | 8 June 2026 |
| Last updated at source | 8 June 2026 |
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