collaborators

17 papers

cs.AI2026

Constrained Adaptive Rejection Sampling

Paweł Parys, Sairam Vaidya, Taylor Berg-Kirkpatrick +1

Language Models (LMs) are increasingly used in applications where generated outputs must satisfy strict semantic or syntactic constraints. Existing approaches to constrained genera…

cs.LG2026

Learning the Error Patterns of Language Models

Jinwoo Kim, Taylor Berg-KirkPatrick, Loris D'Antoni

When generating outputs for domains with specific validity constraints (e.g., a program should compile), LLMs often fail in a small number of focused ways: for example, by using Py…

cs.LG2026

Continuous Diffusion Models Can Obey Formal Syntax

Jinwoo Kim, Taylor Berg-Kirkpatrick, Loris D'Antoni

Diffusion language models offer a promising alternative to autoregressive models due to their global, non-causal generation process, but their continuous latent dynamics make discr…

cs.LG2026

Manifold-Guided Attention Steering

Ian Li, Kapilesh Guruprasad, Raunak Sengupta +3

Large language models frequently produce errors in reasoning tasks despite possessing the underlying knowledge required for correct reasoning. One possible approach to improve reas…

cs.PL2026

Language-Based Agent Control

Timothy Zhou, Loris D'Antoni, Nadia Polikarpova

This paper introduces language-based agent control (LBAC), a new programming model for agentic applications that brings techniques from programming languages and language-based sec…

cs.CL2026

The Format Tax

Ivan Yee Lee, Loris D'Antoni, Taylor Berg-Kirkpatrick

Asking a large language model to respond in JSON should be a formatting choice, not a capability tax. Yet we find that structured output requirements -- JSON, XML, LaTeX, Markdown…