3 citations · 4 across the 14 of their papers we have counts for
17 papers
Guarded Commits: Transactional Human Approvals for LLM Workflows
Laurent Bindschaedler, Ferdi Kossmann, Chunwei Liu +1
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. Th…
Bonded Recourse for Smart-Contract Settlement of Compensable Agent Side Effects
Laurent Bindschaedler, Quentin Botha, Christoph Siebenbrunner
Autonomous agent runtimes execute tool actions that mutate databases, repositories, and cloud services across organizational boundaries. Authorization and local compensation cover…
Agent Flight Recorder: Tamper-Evident Audit Trails with On-Chain Anchoring for Long-Horizon Tool-Using Agents
Laurent Bindschaedler, Quentin Botha, Christoph Siebenbrunner
Long-horizon agents execute thousands of actions, resulting in sequential failures rather than isolated errors. When a coding agent deletes a production database or a prompt inject…
Don't Trust the Code, Check Its Effects: Runtime Refinement for Regenerated Systems Code Under an Adversarial Generator
Jinhao Hu, Ashvin Goel, Laurent Bindschaedler
Recent work uses large language models to generate systems code from specifications, treating the specification as the durable artifact and the implementation as disposable. Regene…
The Irreversibility Budget: Fleet-Level Risk Accounting and Admission Control for Agent Operating Systems
Bardia Mohammadi, Laurent Bindschaedler
Fleets of LLM agents now externalize effects that cannot be fully undone: they move money, deploy code, delete data, and disclose information. Current controls check one effect at…
The Working Set of a Coding Agent: Coherence Debt in Repository-Scale Tasks
Bardia Mohammadi, Lars Klein, Aman Chadha +2
Repository-scale coding requires an agent to keep tests, imports, configuration, and migration rules consistent within a bounded context window. We model this as reconstructing a c…
The Invisible Lottery: How Subtle Cues Steer Algorithm Choice in LLM Code Generation
Akanksha Narula, Mofasshara Binte Rafique, Laurent Bindschaedler
Large language models (LLMs) now generate substantial production code, often for tasks with multiple valid algorithmic solutions. Incidental prompt cues, meaning contextual words o…
Ghost Tool Calls: Issue-Time Privacy for Speculative Agent Tools
Bardia Mohammadi, Lars Klein, Akhil Arora +1
Tool-augmented language agents speculatively issue likely future tool calls to hide latency, but those calls leak inferred user intent to external services before the agent commits…
ClawVM: Harness-Managed Virtual Memory for Stateful Tool-Using LLM Agents
Mofasshara Rafique, Laurent Bindschaedler
Stateful tool-using LLM agents treat the context window as working memory, yet today's agent harnesses manage residency and durability as best-effort, causing recurring failures: l…
Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems
Laurent Bindschaedler
Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies mean rebooting one service can…
Semantic Caching for OLAP via LLM-Based Query Canonicalization (Extended Version)
Laurent Bindschaedler
Analytical workloads exhibit substantial semantic repetition, yet most production caches key entries by SQL surface form (text or AST), fragmenting reuse across BI tools, notebooks…
Grappa: Gradient-Only Communication for Scalable Graph Neural Network Training
Chongyang Xu, Christoph Siebenbrunner, Laurent Bindschaedler
Cross-partition edges dominate the cost of distributed GNN training: fetching remote features and activations per iteration overwhelms the network as graphs deepen and partition co…
Atomix: Timely, Transactional Tool Use for Reliable Agentic Workflows
Bardia Mohammadi, Nearchos Potamitis, Lars Klein +2
LLM agents execute multi-step workflows that mutate external state through tools. Common orchestrators treat tool return as the settlement trigger, so faults, speculation, and conc…
SQL-of-Thought: Multi-agentic Text-to-SQL with Guided Error Correction
Saumya Chaturvedi, Aman Chadha, Laurent Bindschaedler
Converting natural language queries into SQL queries is a crucial challenge in both industry and academia, aiming to increase access to databases and large-scale applications. This…
The Case for Instance-Optimized LLMs in OLAP Databases
Bardia Mohammadi, Laurent Bindschaedler
Large Language Models (LLMs) can enhance analytics systems with powerful data summarization, cleaning, and semantic transformation capabilities. However, deploying LLMs at scale --…
LoRACode: LoRA Adapters for Code Embeddings
Saumya Chaturvedi, Aman Chadha, Laurent Bindschaedler
Code embeddings are essential for semantic code search; however, current approaches often struggle to capture the precise syntactic and contextual nuances inherent in code. Open-so…
Towards Reliable Latent Knowledge Estimation in LLMs: Zero-Prompt Many-Shot Based Factual Knowledge Extraction
Qinyuan Wu, Mohammad Aflah Khan, Soumi Das +7
In this paper, we focus on the challenging task of reliably estimating factual knowledge that is embedded inside large language models (LLMs). To avoid reliability concerns with pr…