holi-lab/ArcANE-Data

ArcANE: Do Role-Playing Language Agents Stay in Character at the Right Time?

🎉 Accepted at EMNLP 2026 (Main)

ArcANE is a benchmark for evaluating phase-aware character role-playing. It contains 570 Character Arcs and 4,854 probes across 19 novels and 87 principal characters. Each arc segments a character’s narrative into phases that capture psychological and behavioral changes, while each probe presents the same scenario across phases to test whether responses evolve consistently.

📊 Dataset Statistics

Configuration	Split	Examples
SFT	train	20,560
SFT	test	2,285
DPO	train	12,746
DPO	test	375
RLVR	train	2,513
RLVR	test	678
Total	train	35,819
Total	test	3,338

📚 Novel Coverage

All three configurations cover the same 10 training novels. The two novels East Lynne and The Underdogs are excluded.

Novel	SFT train	SFT test	DPO train	DPO test	RLVR train	RLVR test
Anne of Green Gables	2,452	272	1,549	44	265	79
Dorian Gray	1,717	191	1,007	32	219	63
Great Expectations	1,312	146	781	27	167	42
Jane_Eyre	2,446	272	1,538	37	288	81
Lady Audley's Secret	1,912	212	1,211	34	237	60
Little Women	2,978	331	1,911	57	356	90
Olaudah Equiano	767	85	457	13	106	28
Persuasion	2,122	236	1,318	33	282	76
Treasure Island	1,968	219	1,186	47	243	76
pride_and_prejudice	2,886	321	1,788	51	350	83
Total	20,560	2,285	12,746	375	2,513	678

🚀 Quick Start

from datasets import load_dataset

REPO_ID = "holi-lab/ArcANE-Data"

sft_dataset = load_dataset(REPO_ID, "sft")
dpo_dataset = load_dataset(REPO_ID, "dpo")
rlvr_dataset = load_dataset(REPO_ID, "rl")

# A split can also be loaded directly.
rlvr_train = load_dataset(
    REPO_ID,
    "rl",
    split="train",
)

print(rlvr_train.features)
print(rlvr_train[0])

🧭 Data Configuration

A source record is canonical when phase_idx == anchor_phase_idx. Other phases are counterfactual: the same character answers the same probe from a different point in their development arc.

                           ┌─ canonical phase ─────── preferred / reference
Novel → Character → Probe ─┤
                           └─ counterfactual phase ── plausible off-phase behavior

1. SFT data

Chat-style supervised examples containing:

• id: unique generation identifier
• source: source novel
• meta_data: character, axis, probe, phase, reference, and generation metadata
• messages: chat-ready [system, user, assistant] conversation

{
    "id": "...",
    "source": "...",
    "meta_data": {
        "character": "...",
        "probe_id": "...",
        "phase_idx": 0,
        "anchor_phase_idx": 0,
        "scenario": "...",
        "question": "...",
    },
    "messages": [
        {"role": "system", "content": "Character and arc context..."},
        {"role": "user", "content": "Scenario and question..."},
        {"role": "assistant", "content": "In-character response..."},
    ],
}

2. DPO data

Conversational preference pairs that contrast canonical behavior with behavior from another phase of the same probe:

• chosen: canonical [system, user, assistant] conversation
• rejected: counterfactual [system, user, assistant] conversation
• metadata: probe identity, phase labels, phase distance, and source IDs

The chosen and rejected sequences share the same canonical system/user prompt; only the assistant response differs.

3. RLVR data

Canonical-phase prompts for optimizing one generated response. The assistant turn is omitted from the policy-visible prompt.

• data_source: reward-routing identifier
• prompt: policy-visible [system, user] conversation
• ability: persona_arc_fidelity
• reward_model: reference style and serialized action/speech/thought target
• extra_info: probe identity, phase data, references, and prompt text

Gold action, speech, and thought remain in reward fields only.

📖 Citation

@misc{song2026arcaneroleplayinglanguageagents,
      title={ArcANE: Do Role-Playing Language Agents Stay in Character at the Right Time?}, 
      author={Woojung Song and Nalim Kim and Sangjun Song and Chaewon Heo and Jongwon Lim and Yohan Jo},
      year={2026},
      eprint={2606.05553},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2606.05553}, 
}