18 citations · 20 across the 19 of their papers we have counts for
7 papers · 1 filter
BEAVER: An Efficient Deterministic LLM Verifier
Tarun Suresh, Nalin Wadhwa, Debangshu Banerjee +1
As large language models (LLMs) transition from research prototypes to production systems, practitioners often need reliable methods to verify model outputs and characterize tail r…
Why DPO is a Misspecified Estimator and How to Fix It
Aditya Gopalan, Sayak Ray Chowdhury, Debangshu Banerjee
Direct alignment algorithms such as Direct Preference Optimization (DPO) fine-tune models based on preference data, using only supervised learning instead of two-stage reinforcemen…
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…
Data Shifts Hurt CoT: A Theoretical Study
Lang Yin, Debangshu Banerjee, Gagandeep Singh
Chain of Thought (CoT) has been applied to various large language models (LLMs) and proven to be effective in improving the quality of outputs. In recent studies, transformers are…
DINGO: Constrained Inference for Diffusion LLMs
Tarun Suresh, Debangshu Banerjee, Shubham Ugare +2
Diffusion LLMs have emerged as a promising alternative to conventional autoregressive LLMs, offering significant potential for improved runtime efficiency. However, existing diffus…
Support is All You Need for Certified VAE Training
Changming Xu, Debangshu Banerjee, Deepak Vasisht +1
Variational Autoencoders (VAEs) have become increasingly popular and deployed in safety-critical applications. In such applications, we want to give certified probabilistic guarant…
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…