HELPER-X: A Unified Instructable Embodied Agent to Tackle Four Interactive Vision-Language Domains with Memory-Augmented Language Models
HELPER-X extends a memory-based language planner with examples, prompts and question-asking APIs. The authors evaluate one embodied agent across several instruction and dialogue benchmarks. It is a bounded baseline for embodied-agent research.
Workflow level n/a Source: Preprint (not peer-reviewed)
Research applicability
HELPER-X extends a memory-based language planner with examples, prompts and question-asking APIs. The authors evaluate one embodied agent across several instruction and dialogue benchmarks. It is a bounded baseline for embodied-agent research.
Getting started
Read the cited abstract and paper; select a relevant task and baseline before trying the approach. This is editorial guidance, not an executed recipe.
Maintenance
Source snapshot checked 2026-11-01; ongoing maintenance, installed behavior and current-version parity not generally verified.
License
Consult original licence and data/provider terms; source access is not reuse clearance. No licence/rights audit or installation was performed.
Workflow & human oversight
Workflow level unassigned: Instructions, memory retrieval, planning and question APIs are described; research oversight and validation checkpoints are unspecified. Human control/boundary: No operational researcher checkpoints established in this abstract.; Instructions, memory retrieval, planning and question APIs are described; research oversight and validation checkpoints are unspecified.
Workflow level is not an evidence score; higher is not better evidence.
Approach
HELPER-X extends a memory-based language planner with examples, prompts and question-asking APIs. The authors evaluate one embodied agent across several instruction and dialogue benchmarks. It is a bounded baseline for embodied-agent research. Documented steps: HELPER-X extends a memory-based language planner with examples, prompts and question-asking APIs. The authors evaluate one embodied agent across several instruction and dialogue benchmarks. It is a bounded baseline for embodied-agent research.; Only the operations expressly described in the abstract are covered; implementation, approvals and stopping rules are not inferred.
Outcomes (as reported by the originating team)
Reported by originating authors, not independently reproduced. No independent reproduction was performed here.
Limitations
Benchmark claims are author-reported; transfer to physical robotics is not established. Abstract-only review; full methods and execution were not verified.
Reproducibility
Primary-source text was read and preserved with provenance hashes. No candidate code, model, benchmark, data upload or claimed outcome was executed/reproduced.
Adoption requirements
Research expertise to evaluate source methods and outputs; task-specific datasets, models, compute, access rights and implementation requirements require checking before use.
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