New Query Engine for Agent Data & MolLingo: Multi-Agent Chemist Reasoning | Midnight Signal AI

Midnight Signal AI — AI news from the last 24 hours. Today's lead: arXiv cs.AI — A Query Engine for the Agents In this episode: - arXiv cs.AI: A Query Engine for the Agents - arXiv cs.AI: MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents - arXiv cs.AI: MIRA: A Bilingual Benchmark for Medical Information Response Audit - arXiv cs.AI: PetroBench: A Benchmark for Large Language Models in Petroleum Engineering - arXiv cs.AI: MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation - arXiv cs.AI: Verifiable Benchmarking of Long-Horizon Spatial Biology - arXiv cs.AI: OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings - arXiv cs.AI: A Matter of TASTE: Improving Coverage and Difficulty of Agent Benchmarks Question: What's the one AI story today that you think most people are missing? Sources (selection): 1. arXiv cs.AI — A Query Engine for the Agents https://arxiv.org/abs/2605.27785 2. arXiv cs.AI — MolLingo: Molecule-Native Representations for LLM-Powered Scientific Agents https://arxiv.org/abs/2605.27853 3. arXiv cs.AI — MIRA: A Bilingual Benchmark for Medical Information Response Audit https://arxiv.org/abs/2605.28025 4. arXiv cs.AI — PetroBench: A Benchmark for Large Language Models in Petroleum Engineering https://arxiv.org/abs/2605.28032 5. arXiv cs.AI — MTAVG-Bench 2.0: Diagnosing Failure Modes of Cinematic Expressiveness in Multi-Talker Audio-Video Generation https://arxiv.org/abs/2605.28035 6. arXiv cs.AI — Verifiable Benchmarking of Long-Horizon Spatial Biology https://arxiv.org/abs/2605.28065 7. arXiv cs.AI — OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings https://arxiv.org/abs/2605.28168 8. arXiv cs.AI — A Matter of TASTE: Improving Coverage and Difficulty of Agent Benchmarks https://arxiv.org/abs/2605.28556 9. arXiv cs.AI — AutoScientists: Self-Organizing Agent Teams for Long-Running Scientific Experimentation https://arxiv.org/abs/2605.28655 10. arXiv cs.AI — The Alignment Floor: When Persona Customization Is Safe https://arxiv.org/abs/2605.27382 11. arXiv cs.AI — Bridging the Stability-Expressivity Gap: Synthetic Data Scaling and Preference Alignment for Low-Resource Spoken Language Models https://arxiv.org/abs/2605.27383 12. arXiv cs.AI — From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons https://arxiv.org/abs/2605.27387 13. arXiv cs.AI — Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis https://arxiv.org/abs/2605.27401 14. arXiv cs.AI — Prominence-Stratified Failure Modes in Retrieval-Augmented Commercial Recommendation: A 37,000-Run Audit https://arxiv.org/abs/2605.27439 15. arXiv cs.AI — On the Subgaussianity of Quantized Linear Maps: An AI-Assisted Note https://arxiv.org/abs/2605.27563 16. arXiv cs.AI — Hallucination Behavior in Multimodal LLMs Across Agricultural Image Interpretation and Generation Tasks https://arxiv.org/abs/2605.27595 17. arXiv cs.AI — Hurwitz Quaternion Multiplicative Quantization for KV Cache Compression https://arxiv.org/abs/2605.27646 18. arXiv cs.AI — Cultural Fidelity in English-to-Hindi Translation: A Preservation-Fluency Frontier for Gender Recoverability https://arxiv.org/abs/2605.27654 19. arXiv cs.AI — CiteCheck: Retrieval-Grounded Detection of LLM Citation Hallucinations in Scientific Text https://arxiv.org/abs/2605.27700 20. arXiv cs.AI — Do Models Know Why They Changed Their Mind? Interpretability and Faithfulness of Chain-of-Thought Under Knowledge Conflict https://arxiv.org/abs/2605.27773 21. arXiv cs.AI — DecomposeRL: Learning to Ask Useful, Informative, and Diverse Questions for Semi-Supervised, Traceable Claim Verification https://arxiv.org/abs/2605.27858 22. arXiv cs.AI — Let the Results Speak: A Replication-First Paradigm for LLM Behavioral Benchmarking https://arxiv.org/abs/2605.27914 23. arXiv cs.AI — Periodic RoPE for Infinite Context LLMs https://arxiv.org/abs/2605.27980 24. arXiv cs.AI — Pruning and Distilling Mixture-of-Experts into Dense Language Models https://arxiv.org/abs/2605.28207 25. arXiv cs.AI — Debate with Images: Detecting Deceptive Behaviors in Multimodal Large Language Models https://arxiv.org/abs/2512.00349 — Automated brief. Reporting may evolve after publication.