Autonomous Research & Recursive Self‑Improvement

The question is no longer speculative. Research agents now synthesize literature, propose hypotheses that have been taken into laboratory testing, and run closed research loops: proposing an idea, implementing it, running an experiment, evaluating the result, and choosing the next attempt. What this establishes is contested: it shows that generated hypotheses can be worth testing, not that novelty has been measured.

Self-improvement also reaches training: models generate practice data, rewards, curricula, and critiques through self-play, self-reward, and verifiable task generation, and agentic data systems improve the datasets they create. This broadens AI-for-AI to data curation, pretraining, midtraining, post-training, and systems optimization. Yet full recursive self-improvement remains unproven; evaluation must expose overfitting, hidden human labor, and reward tampering.

ARRSI fits AACL-IJCNLP because language is how research agents form hypotheses, retrieve multilingual evidence, call tools, critique claims, and explain results. The workshop brings together NLP, agentic systems, AI for Science, AI for AI, evaluation, and governance to establish definitions, benchmarks, reporting standards, and safety boundaries for systems that do not merely produce research-like text, but accumulate auditable evidence and use it to become better researchers.

Submissions are now open on OpenReview. The submission deadline is September 30, 2026, 11:59 PM AoE.

Long papers run up to 8 pages and short, position, or resource papers up to 4 pages, excluding references, in *ACL format. Submissions are double-blind and will be reviewed on OpenReview. Every accepted paper presents a poster, and 4 to 6 receive talk slots. We welcome empirical, theoretical, systems, dataset, benchmark, survey, and position papers. Bring your findings, tools, benchmarks, and carefully documented negative results to the ARRSI community.

We plan to submit the final camera-ready papers to the ACL Anthology proceedings by October 15, 2026.