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ecai-related-work

Use when writing the ECAI related-work section — covering the relevant general-AI lanes (symbolic, learning, multi-agent, application) for a broad r…

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ECAI Related Work

ECAI's related work has a peculiar difficulty: the reviewer pool is broad (a planning paper may

draw a KR reviewer and an ML reviewer), yet the space is tiny — the body is 7 pages and

references overflow into only 1 page (standalone ECAI) or 2 pages (IJCAI-ECAI 2026). You must

position against the right lanes for a general audience and stay compact.

Cover the lanes a general-AI reviewer will expect

Identify which AI lanes your contribution touches and place it in each — a broad reviewer will fault

a section that only cites its author's home subfield:

  • Symbolic / foundational lane — the KR, planning, search, reasoning, or argumentation line

your problem sits in.

  • Learning lane — the ML/statistical methods your work uses or competes with.
  • Multi-agent / decision lane — if agents, game-theoretic, or sequential-decision aspects

apply.

  • Application lane — the real-world domain, especially for a PAIS-flavored contribution.
  • Cross-venue neighbors — the closest work at IJCAI, AAAI, AAMAS, KR, or a specialist venue, so

a reviewer from that community sees you know the field's flagship results.

You will not cover all lanes deeply at 7+1(2) pages — cover the ones your claim actually engages,

and cite the canonical entry point for the rest.

Delta-first positioning

Do not write an annotated bibliography. For each closest competitor, state the delta in one

sentence: what they do, and precisely what you do differently or additionally.

> "Prior learned-heuristic planners plug the model in directly and lose completeness [refs]; we

> preserve completeness and a (1+ε) bound via per-state switching."

Delta-first writing does three jobs at once in minimal space: it credits prior work, states your

novelty, and pre-empts the "how is this different from [X]?" reviewer question.

Keep it double-blind

ECAI is double-blind. Self-citations are the classic leak:

  • Cite your own prior work in the third person ("Smith et al. [7] showed...") — never "in our

previous work [7]."

  • Do not let the density or phrasing of self-citations reveal the author group.
  • Anonymize a system name that identifies you if it appears in the comparison.
# Catch first-person self-citation and identity leaks in related work
grep -nEi 'our (previous|prior|earlier) (work|paper|system|approach)|we previously' paper.tex | head

Budget discipline

  • The reference pages are 1 page (standalone) or 2 pages (IJCAI-ECAI 2026) — finite. Prune

to the works that position the contribution, not every paper you read.

  • Prefer the canonical citation for a well-known result over three secondary ones.
  • Move an extended survey-style discussion to the supplement if it is not decision-critical

(ecai-supplementary); keep the delta-establishing citations in the body.

  • Do not pad the reference list to signal thoroughness — a broad reviewer notices citations that do

no positioning work.

Common failure modes

  • Home-subfield tunnel vision — a planning paper that ignores the learning lane it competes

with, or an ML paper blind to the symbolic literature it reinvents.

  • Bibliography, not positioning — listing works without stating the delta.
  • First-person self-citation breaking double-blind.
  • Missing the obvious neighbor at IJCAI/AAAI/AAMAS/KR that a specialist reviewer will know by

heart.

  • Reference-budget overflow forcing body cuts (ecai-submission).

Output format

[Lanes covered] symbolic / learning / multi-agent / application / cross-venue — which apply, all present?
[Delta statements] each closest competitor -> one-sentence delta? gaps: <list>
[Double-blind] self-citations third-person; no identifying system names? yes/no
[Budget] reference pages within 1 (standalone) / 2 (2026); extended survey moved to supplement?
[Neighbor check] closest IJCAI/AAAI/AAMAS/KR result cited? yes/no

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