From the 1 of 6 linked papers with an AI index.
1 citations · 1 across the 2 of their papers we have counts for
6 papers
DeepLoop: Depth Scaling for Looped Transformers
Shuzhen Li, Yifan Zhang, Jiacheng Guo +2
DeepLoop reuses a compact stack of transformer blocks across multiple passes to increase model depth without adding parameters, and introduces new residual scaling rules to keep tr…
Monadic Context Engineering
Yifan Zhang, Yang Yuan, Mengdi Wang +1
The proliferation of Large Language Models (LLMs) has catalyzed a shift towards autonomous agents capable of complex reasoning and tool use. However, current agent architectures ar…
Interactive Benchmarks
Baoqing Yue, Zihan Zhu, Yutong Han +6
Existing reasoning evaluation paradigms suffer from different limitations: fixed benchmarks are increasingly saturated and vulnerable to contamination, while preference-based evalu…
CryptoBench: A Dynamic Benchmark for Expert-Level Evaluation of LLM Agents in Cryptocurrency
Jiacheng Guo, Suozhi Huang, Zixin Yao +16
This paper introduces CryptoBench, the first expert-curated, dynamic benchmark designed to rigorously evaluate the real-world capabilities of Large Language Model (LLM) agents in t…
Deep Delta Learning
Yifan Zhang, Yifeng Liu, Mengdi Wang +1
Transformer residual streams evolve through additive updates. Although a sufficiently expressive residual block can represent content replacement, standard architectures do not par…
Web World Models
Jichen Feng, Yifan Zhang, Chenggong Zhang +3
Language agents increasingly require persistent worlds in which they can act, remember, and learn. Existing approaches sit at two extremes: conventional web frameworks provide reli…