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20212026
most citedOn The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability

6 citations · 16 across the 15 of their papers we have counts for

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cs.AI2026

Occamy-1.0: Open Pareto-frontier 35B Intelligence for Co-work

Wenhui Chen, Shiwen Cheng, Hao Dong +39

Co-work agents execute complex workflows that combine information gathering, tool use, coding, and file manipulation across many model invocations. Because cost and latency accumul…

cs.AI2026

The Optimizer Is the Agent: Reasoning-Driven Search across Prompts, Programs, and ML Workflows

Junbo Li, Boyi Liu, Canwen Xu +5

Recent systems for optimizing prompts, programs, and ML workflows typically rely on explicit outer-loop controllers such as evolutionary search, bandits, or textual-gradient method…

cs.AI2026

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems

Jianing Zhu, Yeonju Ro, John Robertson +5

Long-lived AI agents are increasingly deployed as persistent operational systems, yet they are still evaluated like freshly initialized models. Day-one benchmarks miss a basic syst…

cs.AI2026

Neurosymbolic LoRA: Why and When to Tune Weights vs. Rewrite Prompts

Kevin Wang, Neel P. Bhatt, Cong Liu +7

Large language models (LLMs) can be adapted either through numerical updates that alter model parameters or symbolic manipulations that work on discrete prompts or logical constrai…

cs.AI2024★ 6 cited

On The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability

Kevin Wang, Junbo Li, Neel P. Bhatt +4

Recent advancements in Large Language Models (LLMs) have showcased their ability to perform complex reasoning tasks, but their effectiveness in planning remains underexplored. In t…