7 papers
Survey on Evaluation of LLM-based Agents
Asaf Yehudai, Lilach Eden, Alan Li +5
LLM-based agents represent a paradigm shift in AI, enabling autonomous systems to plan, reason, and use tools while interacting with dynamic environments. This paper provides the f…
Textual Planning with Explicit Latent Transitions
Eliezer Shlomi, Ido Levy, Eilam Shapira +6
Planning with LLMs is bottlenecked by token-by-token generation and repeated full forward passes, making multi-step lookahead and rollout-based search expensive in latency and comp…
Towards Enforcing Company Policy Adherence in Agentic Workflows
Naama Zwerdling, David Boaz, Ella Rabinovich +3
Large Language Model (LLM) agents hold promise for a flexible and scalable alternative to traditional business process automation, but struggle to reliably follow complex company p…
Effective Red-Teaming of Policy-Adherent Agents
Itay Nakash, George Kour, Koren Lazar +3
Task-oriented LLM-based agents are increasingly used in domains with strict policies, such as refund eligibility or cancellation rules. The challenge lies in ensuring that the agen…
CRISP: Complex Reasoning with Interpretable Step-based Plans
Matan Vetzler, Koren Lazar, Guy Uziel +3
Recent advancements in large language models (LLMs) underscore the need for stronger reasoning capabilities to solve complex problems effectively. While Chain-of-Thought (CoT) reas…
OASBuilder: Generating OpenAPI Specifications from Online API Documentation with Large Language Models
Koren Lazar, Matan Vetzler, Kiran Kate +8
AI agents and business automation tools interacting with external web services require standardized, machine-readable information about their APIs in the form of API specifications…