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20232026
most citedThe Generative AI Paradox: "What It Can Create, It May Not Understand"

10 citations · 15 across the 9 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.AI2026

World of SWECraft: Agent Collaboration at Scale via Simulated Software Worlds

Shannon Zejiang Shen, Yapei Chang, Qiyao Liang +13

As teams of AI agents take on larger projects and long-standing open problems, agent collaboration offers another dimension for scaling inference-time compute. To understand what m…

cs.CL2026

Realize What Matters: Principled Context Representation for Large-Scale Reasoning

Michael Theologitis, Dean Light, Shuyue Stella Li +3

Solving complex tasks in domains such as science, medicine, law, and finance often requires assembling interdependent information scattered across vast, heterogeneous sources far b…

cs.CL2026

Deep Reasoning in General Purpose Agents via Structured Meta-Cognition

Dean Light, Michael Theologitis, Kshitish Ghate +7

Humans intuitively solve complex problems by flexibly shifting among reasoning modes: they plan, execute, revise intermediate goals, resolve ambiguity through associative judgment,…

cs.LG2026

Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG

Seungju Han, Konwoo Kim, Chanwoo Park +5

Synthetic data augmentation helps language models learn new knowledge in data-constrained domains. However, naively scaling existing synthetic data methods by training on more synt…

cs.CL2026

FDARxBench: Benchmarking Regulatory and Clinical Reasoning on FDA Generic Drug Assessment

Betty Xiong, Jillian Fisher, Benjamin Newman +5

We introduce an expert curated, real-world benchmark for evaluating document-grounded question-answering (QA) motivated by generic drug assessment, using the U.S. Food and Drug Adm…