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Author

Laurent Bindschaedler

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Review Sep 2026

Guarded Commits: Transactional Human Approvals for LLM Workflows

LLM workflows often require human approval before an irreversible external action. Most systems keep that approval outside the workflow, as an interface click or an audit entry. The workflow therefore lacks a commit-time check that every risky path reached an approval gate. Its logs may not preserve the reviewed eviden...

Laurent Bindschaedler, Ferdinand Kossmann, Chun-Wei Liu et al. · 0 citations
Preprint Sep 2026

Bonded Recourse for Smart-Contract Settlement of Compensable Agent Side Effects

Autonomous agent runtimes execute tool actions that mutate databases, repositories, and cloud services across organizational boundaries. Authorization and local compensation cover pre-action admission and in-runtime rollback, but neither settles the residual harm left after a permitted action fails. We design Recourse,...

Laurent Bindschaedler, Quentin Botha, Christoph Siebenbrunner · 2 citations
Preprint Aug 2026

The Working Set of a Coding Agent: Coherence Debt in Repository-Scale Tasks

This work reconstructs a coupled-fact graph as reconstructing a coupled-fact graph: at each edit, a required fact comes from recent context or parametric memory, and the facts covered by neither form coherence debt.

Bardia Mohammadi, L. Klein, Aman Chadha et al. · 3 citations
Preprint Sep 2026

Agent Flight Recorder: Tamper-Evident Audit Trails with On-Chain Anchoring for Long-Horizon Tool-Using Agents

The Agent Flight Recorder captures each agent action as a structured, canonically serialized event binding eight semantic fields from intent through execution to provenance, and periodic on-chain anchoring of epoch roots lets any verifier with the disclosed payload and Merkle proof check the record independently, witho...

Laurent Bindschaedler, Quentin Botha, Christoph Siebenbrunner · 4 citations
#small language model Open access Sep 2026

IOLM-DB: Instance-optimized large language model execution for column-scale semantic operators

Large language models (LLMs) can implement row-level semantic transformations over tabular data, but a general-purpose model reserves the same accelerator resources even when every row uses one fixed prompt. IOLM-DB compiles that recurring prompt–column pair into an operator sized to the work it actually does. It sampl...

Bardia Mohammadi, Laurent Bindschaedler · 0 citations

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