11 citations · 20 across the 12 of their papers we have counts for
8 papers · 1 filter
History Replays Itself: Unleashing Long-Context Capability in Linear Attention
Li Nanbo, Firas Laakom, Yilan Zhang +10
Linear attention promises the efficiency needed for long-context language modelling, yet its fixed-size recurrent state must simultaneously support ongoing computation and preserve…
Self-Improvements in Modern Agentic Systems: A Survey
Zhe Ren, Yimeng Chen, Dandan Guo +9
Self-improving autonomous agents are moving from research prototypes to deployed systems. The primary goal is controllable evolution, or adaptation, from experience with minimal or…
Huxley-Gödel Machine: Human-Level Coding Agent Development by an Approximation of the Optimal Self-Improving Machine
Wenyi Wang, Piotr Piękos, Li Nanbo +5
Recent studies operationalize self-improvement through coding agents that edit their own codebases. They grow a tree of self-modifications through expansion strategies that favor h…
How to Correctly do Semantic Backpropagation on Language-based Agentic Systems
Wenyi Wang, Hisham A. Alyahya, Dylan R. Ashley +4
Language-based agentic systems have shown great promise in recent years, transitioning from solving small-scale research problems to being deployed in challenging real-world tasks.…
Agent-as-a-Judge: Evaluate Agents with Agents
Mingchen Zhuge, Changsheng Zhao, Dylan Ashley +10
Contemporary evaluation techniques are inadequate for agentic systems. These approaches either focus exclusively on final outcomes -- ignoring the step-by-step nature of agentic sy…
FACTS: A Factored State-Space Framework For World Modelling
Li Nanbo, Firas Laakom, Yucheng Xu +2
World modelling is essential for understanding and predicting the dynamics of complex systems by learning both spatial and temporal dependencies. However, current frameworks, such…
Data Interpreter: An LLM Agent For Data Science
Sirui Hong, Yizhang Lin, Bang Liu +24
Large Language Model (LLM)-based agents have shown effectiveness across many applications. However, their use in data science scenarios requiring solving long-term interconnected t…
Language Agents as Optimizable Graphs
Mingchen Zhuge, Wenyi Wang, Louis Kirsch +3
Various human-designed prompt engineering techniques have been proposed to improve problem solvers based on Large Language Models (LLMs), yielding many disparate code bases. We uni…