Distilling Game Code World Model Generation into Lightweight Large Language Models
1 distinct publishers across 2 articles (some outlets filed more than once).
Ownership mix: Other: 2
1 publishers · 2 articles · switch to 1-minute for disagreement and framing.
What happened
Large Language Models (LLMs) have shown great ability in generating executable code from natural language, opening the possibility of automatically constructing environments for AI agents. Recent work on Code World…
Why the coverage differs
AI-assisted comparison · labeled · generated just generated or not yet stored · not a verdict
What happened: Evaluating Large Language Models in a Complex Hidden Role Game
Where coverage diverges: Center: 2 (arXiv cs.AI, arXiv cs.AI).
Comparison summary
AI-assisted · Cerebras / Llama · just generated or not yet stored · inspect sources below rather than trusting this alone
What happened: Evaluating Large Language Models in a Complex Hidden Role Game
Where coverage diverges: Center: 2 (arXiv cs.AI, arXiv cs.AI).
What's missing: AI bias-comparison is temporarily offline. Configure Cerebras in admin to enable rich comparison summaries.
Report timeline
Oldest → newest among clustered members. Gaps may mean delayed pickup, not silence.
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May 24, 2026, 9:00 PMarXiv cs.AI · CenterEvaluating Large Language Models in a Complex Hidden Role Game
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May 25, 2026, 9:00 PMarXiv cs.AI · CenterDistilling Game Code World Model Generation into Lightweight Large Language Models
Coverage by perspective
Perspective labels are external consensus ratings (AllSides / Ad Fontes / MBFC-style), not WeSearch truth scores. Center is not automatically more accurate.
Center · 2
Headline framing
Vocabulary fingerprints · not a political endorsement
AI framing analysis temporarily offline. Configure Cerebras in admin to enable framing comparison.
Bias/ownership: published methodology on source profiles · AI text always labeled · no reader paywall · no engagement ranking of news · transparency · contribute Ws · home