The task
How could a lightweight agent decide when to retrieve, bridge languages, and produce grounded answers with an evaluation method that agrees with human judgments?
Projected solution
I propose a budget-aware retrieval controller paired with a separately evaluated judging framework for relevance, attribution, completeness, and cross-lingual faithfulness.
The design compares fixed retrieval with selective retrieval, query reformulation, and cross-lingual retrieval under matched budgets. Human labels and reserved test queries anchor evaluation. Judge consistency, language effects, and sensitivity to answer order would be measured separately from answer quality.
Proposed workflow
Proposed: multilingual retrieval · bounded agents · judge calibration- 01
Retrieve
Select and reformulate queries under a fixed retrieval and inference budget.
- 02
Ground
Connect answer claims to passages across the query and document languages.
- 03
Evaluate
Compare retrieval and answer outcomes with reserved labels and calibrated judging.
Implementation roadmap
Proposed milestones / Not started- Define and freeze. Specify the task, data rights, baselines, evaluation criteria, and reserved test material.
- Build the smallest end-to-end study. Implement the proposed workflow with traceable inputs and reproducible outputs.
- Compare and stress-test. Run controlled baseline comparisons and ablations; inspect failure modes and resource use.
- Reproduce and report. Repeat the study from a clean environment and publish measured findings with supporting artifacts.
The research proposal expands these milestones into project-specific methods, experimental controls, and deliverables.
Methods / evidence / reproduction
Read the research.
The proposed study uses task-appropriate TREC resources, paired comparisons, language-stratified reporting, and ablations of agent decisions. Dataset access, splits, and labeling would be fixed before experiments.
The proposal develops the research question, proposed method, evaluation design, and phased roadmap. Its GitHub directory contains the planning documents. No implementation or experimental results are claimed.