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cs.PL2025
Evolving Abstract Transformers for Gradient-Guided, Adaptable Abstract Interpretation
Shaurya Gomber, Debangshu Banerjee, Gagandeep Singh
Current numerical abstract interpretation relies on fixed, hand-crafted, instruction-specific transformers tailored to each domain, causing three key limitations: transformers cann…
cs.PL2025
CRANE: Reasoning with constrained LLM generation
Debangshu Banerjee, Tarun Suresh, Shubham Ugare +2
Code generation, symbolic math reasoning, and other tasks require LLMs to produce outputs that are both syntactically and semantically correct. Constrained LLM generation is a prom…