AniME: Adaptive Multi-Agent Planning for Long Animation Generation arXiv:2508.18781v2 Announce Type: replace Abstract: We present AniME, a director-oriented multi-agent system for automated long-form anime production, covering the full workflow from a story to the final video. The director agent keeps…
Skill-based Explanations for Serendipitous Course Recommendation arXiv:2508.19569v1 Announce Type: new Abstract: Academic choice is crucial in U.S. undergraduate education, allowing students significant freedom in course selection. However, navigating the complex academic environment is challenging due to limited information, guidance, and…
ReST-RL: Achieving Accurate Code Reasoning of LLMs with Optimized Self-Training and Decoding arXiv:2508.19576v1 Announce Type: new Abstract: With respect to improving the reasoning accuracy of LLMs, the representative reinforcement learning (RL) method GRPO faces failure due to insignificant reward variance,…
Caught in the Act: a mechanistic approach to detecting deception arXiv:2508.19505v1 Announce Type: new Abstract: Sophisticated instrumentation for AI systems might have indicators that signal misalignment from human values, not unlike a “check engine” light in cars. One such indicator…
Democracy-in-Silico: Institutional Design as Alignment in AI-Governed Polities arXiv:2508.19562v1 Announce Type: new Abstract: This paper introduces Democracy-in-Silico, an agent-based simulation where societies of advanced AI agents, imbued with complex psychological personas, govern themselves under different institutional frameworks. We explore what…
SLIM: Subtrajectory-Level Elimination for More Effective Reasoning arXiv:2508.19502v1 Announce Type: new Abstract: In recent months, substantial progress has been made in complex reasoning of Large Language Models, particularly through the application of test-time scaling. Notable examples include o1/o3/o4 series and…
Reliable Weak-to-Strong Monitoring of LLM Agents arXiv:2508.19461v1 Announce Type: new Abstract: We stress test monitoring systems for detecting covert misbehavior in autonomous LLM agents (e.g., secretly sharing private information). To this end, we systematize a monitor red teaming (MRT) workflow…
Quantized but Deceptive? A Multi-Dimensional Truthfulness Evaluation of Quantized LLMs arXiv:2508.19432v1 Announce Type: new Abstract: Quantization enables efficient deployment of large language models (LLMs) in resource-constrained environments by significantly reducing memory and computation costs. While quantized LLMs often maintain performance…
AI-Powered Detection of Inappropriate Language in Medical School Curricula arXiv:2508.19883v1 Announce Type: cross Abstract: The use of inappropriate language — such as outdated, exclusionary, or non-patient-centered terms — medical instructional materials can significantly influence clinical training, patient interactions, and health…
Instructional Agents: LLM Agents on Automated Course Material Generation for Teaching Faculties arXiv:2508.19611v1 Announce Type: new Abstract: Preparing high-quality instructional materials remains a labor-intensive process that often requires extensive coordination among teaching faculty, instructional designers, and teaching assistants. In this…
