2 citations · 3 across the 11 of their papers we have counts for
12 papers
On Language Drift during RLVR Post-Training
Michael Sullivan, Alexander Koller
Recent advances in LLM reasoning models---driven primarily by the paradigm of post-training via reinforcement learning with verifiable reward (RLVR)---have enabled them to accompli…
TEVI: Text-Conditioned Editing of Visual Representations via Sparse Autoencoders for Improved Vision-Language Alignment
Sweta Mahajan, Sukrut Rao, Jiahao Xie +2
Vision-language models such as CLIP are highly useful for diverse tasks due to their shared image-text embedding space. Despite this, the image and text embeddings are often poorly…
Accelerating Constrained Decoding with Token Space Compression
Michael Sullivan, Alexander Koller
To guarantee that an LLM's outputs conform to a specified structure, context-free grammar (CFG) decoding engines force the selection of next tokens to produce strings that conform…
LLMs Generate Kitsch
Xenia Klinge, Stefan Ortlieb, Alexander Koller
Large Language Models (LLMs) are increasingly used to generate pictures, texts, music, videos, and other works that have traditionally required human creativity. LLM-generated arti…
AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing
Sarubi Thillainathan, Ji-Ung Lee, Michael Sullivan +1
The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning of the original text. Existing style transfer methods tra…
Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions
Luisa Geiger, Mareike Hartmann, Michael Sullivan +1
In this paper, we propose a novel, automatic tree-based evaluation metric for LLM-generated step-by-step assembly instructions, that more accurately reflects spatiotemporal aspects…
GRPO is Secretly a Process Reward Model
Michael Sullivan, Alexander Koller
Process reward models (PRMs) allow for fine-grained credit assignment in reinforcement learning (RL), and seemingly contrast with outcome reward models (ORMs), which assign a singl…
Procedural Environment Generation for Tool-Use Agents
Michael Sullivan, Mareike Hartmann, Alexander Koller
Although the power of LLM tool-use agents has ignited a flurry of recent research in this area, the curation of tool-use training data remains an open problemespecially for onli…
A Survey on Complex Tasks for Goal-Directed Interactive Agents
Mareike Hartmann, Alexander Koller
Goal-directed interactive agents, which autonomously complete tasks through interactions with their environment, can assist humans in various domains of their daily lives. Recent a…
Learning Program Behavioral Models from Synthesized Input-Output Pairs
Tural Mammadov, Dietrich Klakow, Alexander Koller +1
We introduce Modelizer - a novel framework that, given a black-box program, learns a model from its input/output behavior using neural machine translation algorithms. The resulting…
ADaPT: As-Needed Decomposition and Planning with Language Models
Archiki Prasad, Alexander Koller, Mareike Hartmann +4
Large Language Models (LLMs) are increasingly being used for interactive decision-making tasks requiring planning and adapting to the environment. Recent works employ LLMs-as-agent…
Closing the Curious Case of Neural Text Degeneration
Matthew Finlayson, John Hewitt, Alexander Koller +2
Despite their ubiquity in language generation, it remains unknown why truncation sampling heuristics like nucleus sampling are so effective. We provide a theoretical explanation fo…