Papers with fine-tuning-based approach
Can a Large Language Model Keep My Secrets? A Study on LLM-Controlled Agents (2025.acl-srw)
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| Challenge: | Using large language models, agents can assist with natural language tasks when given access to confidential data. |
| Approach: | They created a synthetic dataset consisting of confidentiality-aware planning and deduction tasks in organizational access control. |
| Outcome: | The proposed model can perform tasks similar to humans when given access to confidential data. |
LLMs are Brittle to Simple Code Transformations: Introducing CETBench – A Benchmark for Code-Equivalence Checking (2026.findings-acl)
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| Challenge: | a new benchmarking tool for code equivalence checks the performance of LLMs. |
| Approach: | They propose a code-equivalence with transformations benchmark built from a repository of programs that may solve the same or different tasks. |
| Outcome: | The proposed approach boosts performance on the transformed pairs of programs. |