3 citations · 7 across the 13 of their papers we have counts for
16 papers
JevGPT: Thinking Fast and Slow in Autonomous Research
Yasheng Sun, Yanning Dai, Yimeng Chen +9
Autonomous research agents must acquire and reason over evidence within a limited budget. Yet relevant sources can remain uninspected or unused, leaving a gap between retrieval cov…
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…
Creation begins with understanding: LLMs as strategy designers for privacy-preserving tabular data synthesis
Jinmeng Li, Quan Zhang, Hangting Ye +4
Sharing tabular data in high-stakes domains is constrained by privacy regulations. Synthetic data offer a promising alternative, but deep generative models are costly to train and…
DiG-bench: Discovery in Games
Ruairidh M. Battleday, Kai Sandbrink, Jimi Cullen-Drohan +13
Discovery---formulating novel generalizations---is a central part of the scientific process. Despite its importance, there is a gap in the current AI benchmark landscape, with few…
Self-State Attacks on Self-Hosted AI Agents: How Far Can OS Defenses Go?
Yimeng Chen, Nathanaël Denis, Roberto Di Pietro +1
Self-hosted AI agents maintain persistent memory, instructions, and configuration that influence their future behavior. If an agent is compromised, an attacker can exploit the agen…
SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions
Yasheng Sun, Zezi Zeng, Yifan Yang +4
Editing the figures in a research paper is a routine and time-consuming part of everyday research practice: authors relabel components, rearrange panels, and restyle visuals as the…
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…
How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation
Yimeng Chen, Zhe Ren, Firas Laakom +3
Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that attacker-published pages are tra…
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…
PhysGym: Benchmarking LLMs in Interactive Physics Discovery with Controlled Priors
Yimeng Chen, Piotr Piȩkos, Mateusz Ostaszewski +2
Evaluating the scientific discovery capabilities of large language model based agents, particularly how they cope with varying environmental complexity and utilize prior knowledge,…
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective
Firas Laakom, Haobo Chen, Jürgen Schmidhuber +1
Despite substantial progress in promoting fairness in high-stake applications using machine learning models, existing methods often modify the training process, such as through reg…
Beyond Outlining: Heterogeneous Recursive Planning for Adaptive Long-form Writing with Language Models
Ruibin Xiong, Yimeng Chen, Dmitrii Khizbullin +2
Long-form writing agents require flexible integration and interaction across information retrieval, reasoning, and composition. Current approaches rely on predefined workflows and…
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…
ScholarChemQA: Unveiling the Power of Language Models in Chemical Research Question Answering
Xiuying Chen, Tairan Wang, Taicheng Guo +7
Question Answering (QA) effectively evaluates language models' reasoning and knowledge depth. While QA datasets are plentiful in areas like general domain and biomedicine, academic…
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…