Source note2 min read
Entity Binding Failures in Tool-Augmented Agents
Source
arXiv
arxiv.org/abs/2606.30531v1
Source
- Source name: arXiv
- Source kind: paper
- Authors / organization: Rahul Suresh Babu, Shashank Indukuri
- Venue: arXiv: cs.AI
- Published: 2026-06-29
- Collected: 2026-06-30
- URL: http://arxiv.org/abs/2606.30531v1
- PDF: https://arxiv.org/pdf/2606.30531v1
- DOI: UNKNOWN
Plain-Language Brief
This research paper focuses on a problem in tool-augmented language model agents called 'entity binding failures'. These failures occur when an agent performs actions incorrectly even though it has chosen the right tool. Examples include contacting the wrong person, attaching the wrong document, or updating the wrong customer account. The paper proposes several methods to address this issue and reports that these methods significantly reduce wrong-entity actions but may slow down task completion.
What the Document Says
- The paper discusses entity binding failures as a reliability and safety problem in tool-augmented agents.
- It introduces a taxonomy of wrong-entity failures in enterprise workflows.
- Several entity-aware execution mechanisms are evaluated, including preconditions, confidence-gated binding, clarification under ambiguity, and provenance tracking.
- In a controlled evaluation, all methods achieved zero wrong-tool errors but produced wrong-entity actions in 24.0-26.0% of runs.
Key Concepts Mentioned
- Tool-augmented agents
- Entity binding failures
- Enterprise workflows
- Entity-aware execution mechanisms
Claims Made by the Document
- Safe tool use requires not only selecting the correct tool, but also reliably binding natural-language references to the correct real-world entity before action.
- Entity-aware methods eliminate wrong-entity actions and reduce risk-weighted wrong-entity exposure.
Evidence Used
- The controlled diagnostic evaluation across various tasks, model backends, and tool-use methods.
Methods / Approach
UNKNOWN
Limitations Stated by the Authors
UNKNOWN
Limitations Noted by the Agent
Agent interpretation — not from the source.
UNKNOWN
Open Questions
UNKNOWN
Notes for Future Q&A
May include interpretation. Labeled where it does.
UNKNOWN
Raw Abstract / Excerpt
Tool-augmented language-model agents are often evaluated by whether they select the correct tool, produce valid API arguments, and complete the requested task. However, an agent may choose the right tool and still act on the wrong external entity. For example, a request to 'email Alex about the launch' may lead the agent to contact the wrong Alex, attach the wrong launch document, reply in the wrong thread, or update the wrong customer account. We call these errors entity binding failures. This paper studies entity binding failures as a distinct reliability and safety problem in tool-augmented agents. We formalize the separation between tool correctness and entity correctness, introduce a taxonomy of wrong-entity failures in enterprise workflows, and evaluate entity-aware execution mechanisms including entity-resolution preconditions, confidence-gated binding, clarification under ambiguity, and provenance tracking. In a controlled diagnostic evaluation across 60 tasks, five model backends, and six tool-use methods, all methods achieved 0.0 percent wrong-tool error, yet action-oriented baselines still produced wrong-entity actions in 24.0-26.0 percent of runs. Entity-aware methods eliminated wrong-entity actions and risk-weighted wrong-entity exposure in this setting, but reduced direct task completion by deferring under ambiguity. These findings show that safe tool use requires not only selecting the correct tool, but also reliably binding natural-language references to the correct real-world entity before action.
