3 papers
cs.CL2026
Recovering Diversity Without Losing Alignment: A DPO Recipe for Post-Trained LLMs
Vinay Samuel, Yapei Chang, Mohit Iyyer
Many open-ended instructions have multiple valid answers that users can benefit from seeing, but post-training often narrows an LLM's output space toward a small set of canonical r…
cs.CL2025
CIE: Controlling Language Model Text Generations Using Continuous Signals
Vinay Samuel, Harshita Diddee, Yiming Zhang +1
Aligning language models (LMs) with user intent is becoming increasingly relevant to enhance user experience. This calls for designing methods that can allow users to control the p…
cs.CL2025
NoveltyBench: Evaluating Language Models for Humanlike Diversity
Yiming Zhang, Harshita Diddee, Susan Holm +5
Language models have demonstrated remarkable capabilities on standard benchmarks, yet they struggle increasingly from mode collapse, the inability to generate diverse and novel out…