6 papers
Spectral Distillation: From Nonlinear Dynamics to Linear State-Space Models
Liane Galanti, Devan Shah, Shlomo Fortgang +1
Can nonlinear dynamical systems be learned through a compact linear state-space representation, without directly solving a non-convex system-identification problem? We give a prova…
Addressing the Orchestration Gap in Generalist Robots via Physical Agency
Liane Galanti, Dhruv Shah, Tri Dao
General-purpose robots need to reason about their actions, combining perception, world knowledge, planning, success detection, recovery, and low-level control. Today's state-of-the…
AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systems
Hadar Mulian, Sergey Zeltyn, Ido Levy +3
We introduce a comprehensive validation framework for LLM-based agentic systems that provides systematic diagnosis and improvement of reliability failures. The framework includes f…
On the Expressivity of Selective State-Space Layers: A Multivariate Polynomial Approach
Edo Cohen-Karlik, Itamar Zimerman, Liane Galanti +3
Recent advances in efficient sequence modeling have introduced selective state-space layers, a key component of the Mamba architecture, which have demonstrated remarkable success i…
From Grounding to Planning: Benchmarking Bottlenecks in Web Agents
Segev Shlomov, Ben wiesel, Aviad Sela +3
General web-based agents are increasingly essential for interacting with complex web environments, yet their performance in real-world web applications remains poor, yielding extre…
Intelligence Analysis of Language Models
Liane Galanti, Ethan Baron
In this project, we test the effectiveness of Large Language Models (LLMs) on the Abstraction and Reasoning Corpus (ARC) dataset. This dataset serves as a representative benchmark…