5 papers
Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge
Arda Uzunoglu, Benjamin Van Durme, Daniel Khashabi
Large language models are increasingly trained and deployed with long contexts that span documents, code repositories, and interaction histories. This scaling reflects the implicit…
Trust Functions: Near-Lossless Weak-to-Strong Generalization by Learning When to Trust the Weak Teacher
Arda Uzunoglu, Alvin Zhang, Daniel Khashabi
Weak-to-strong generalization studies how to improve a strong student using supervision from a weaker teacher when reliable labels are scarce. We view this primarily as a data sele…
World-in-World: World Models in a Closed-Loop World
Jiahan Zhang, Muqing Jiang, Nanru Dai +14
Generative world models (WMs) can now simulate worlds with striking visual realism, which naturally raises the question of whether they can endow embodied agents with predictive pe…
Instructional Text Across Disciplines: A Survey of Representations, Downstream Tasks, and Open Challenges Toward Capable AI Agents
Abdulfattah Safa, Tamta Kapanadze, Arda Uzunoğlu +1
Recent advances in large language models have demonstrated promising capabilities in following simple instructions through instruction tuning. However, real-world tasks often invol…
WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment
Jiefu Ou, Arda Uzunoglu, Benjamin Van Durme +1
AI systems make decisions in physical environments through primitive actions or affordances that are accessed via API calls. While deploying AI agents in the real world involves nu…