activity
20242026
most citedNeural Cellular Automata for ARC-AGI

1 citations · 2 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SI2026

CrossWeave: Bridging Perspectives Across Online Communities with a Dual-Pane Design

Fei Fang, Reva Hirave, William Jurayj +19

Social media systems typically display conversations among already familiar contributors, which can be predictable and one-sided. In civic discourse, this design narrows discussion…

cs.AI2025

A Formal Comparison Between Chain of Thought and Latent Thought

Kevin Xu, Issei Sato

Chain of thought (CoT) elicits reasoning in large language models by explicitly generating intermediate tokens. In contrast, latent thought reasoning operates directly in the conti…

cs.NE2025★ 1 cited

Neural Cellular Automata for ARC-AGI

Kevin Xu, Risto Miikkulainen

Cellular automata and their differentiable counterparts, Neural Cellular Automata (NCA), are highly expressive and capable of surprisingly complex behaviors. This paper explores ho…

cs.LG2025

To CoT or To Loop? A Formal Comparison Between Chain-of-Thought and Looped Transformers

Kevin Xu, Issei Sato

Chain-of-Thought (CoT) and Looped Transformers have been shown to empirically improve performance on reasoning tasks and to theoretically enhance expressivity by recursively increa…

cs.CL2024

Revisiting Absence withSymptoms that *T* Show up Decades Later to Recover Empty Categories

Emily Chen, Nicholas Huang, Casey Robinson +3

This paper explores null elements in English, Chinese, and Korean Penn treebanks. Null elements contain important syntactic and semantic information, yet they have typically been t…

cs.SE2024

Improving Performance of Commercially Available AI Products in a Multi-Agent Configuration

Cory Hymel, Sida Peng, Kevin Xu +1

In recent years, with the rapid advancement of large language models (LLMs), multi-agent systems have become increasingly more capable of practical application. At the same time, t…

cs.LG2024

On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding

Kevin Xu, Issei Sato

Looped Transformers provide advantages in parameter efficiency, computational capabilities, and generalization for reasoning tasks. However, their expressive power regarding functi…

cs.AI2024★ 1 cited

Tur[k]ingBench: A Challenge Benchmark for Web Agents

Kevin Xu, Yeganeh Kordi, Tanay Nayak +7

Can advanced multi-modal models effectively tackle complex web-based tasks? Such tasks are often found on crowdsourcing platforms, where crowdworkers engage in challenging micro-ta…