5 papers
ProofBridge: Auto-Formalization of Natural Language Proofs in Lean via Joint Embeddings
Prithwish Jana, Kaan Kale, Ahmet Ege Tanriverdi +3
Translating human-written mathematical theorems and proofs from natural language (NL) into formal languages (FLs) like Lean 4 has long been a significant challenge for AI. Most sta…
TerraFormer: Automated Infrastructure-as-Code with LLMs Fine-Tuned via Policy-Guided Verifier Feedback
Prithwish Jana, Sam Davidson, Bhavana Bhasker +3
Automating Infrastructure-as-Code (IaC) is challenging, and large language models (LLMs) often produce incorrect configurations from natural language (NL). We present TerraFormer,…
RLSF: Fine-tuning LLMs via Symbolic Feedback
Piyush Jha, Prithwish Jana, Pranavkrishna Suresh +2
Large Language Models (LLMs) have transformed AI but often struggle with tasks that require domain-specific reasoning and logical alignment. Traditional fine-tuning methods do not…
Abstractions-of-Thought: Intermediate Representations for LLM Reasoning in Hardware Design
Matthew DeLorenzo, Kevin Tieu, Prithwish Jana +4
Large language models (LLMs) have achieved impressive proficiency on logic and programming tasks, often rivaling expert-level performance. However, generating functionally correct…
CoTran: An LLM-based Code Translator using Reinforcement Learning with Feedback from Compiler and Symbolic Execution
Prithwish Jana, Piyush Jha, Haoyang Ju +3
In this paper, we present an LLM-based code translation method and an associated tool called CoTran, that translates whole-programs from one high-level programming language to anot…