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20232026
most citedOn The Planning Abilities of OpenAI's o1 Models: Feasibility, Optimality, and Generalizability

6 citations · 10 across the 14 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

@skills: Attention is all you have

Li Yin, Zhi Li, Zhan Shi +4

There are 56,804 public agent skills today, and teams write many more privately. The dominant delivery model is installation: once installed, a skill's description remains in the s…

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.AI2025

Foundation Models for Logistics: Toward Certifiable, Conversational Planning Interfaces

Yunhao Yang, Neel P. Bhatt, Christian Ellis +4

Logistics operators, from battlefield coordinators re-routing airlifts ahead of a storm to warehouse managers juggling late trucks, need to make mission-critical decisions. Prevail…

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…

cs.AI2023★ 1 cited

Fine-Tuning Language Models Using Formal Methods Feedback

Yunhao Yang, Neel P. Bhatt, Tyler Ingebrand +4

Although pre-trained language models encode generic knowledge beneficial for planning and control, they may fail to generate appropriate control policies for domain-specific tasks.…