🎉 Accepted at NeurIPS 2026! Rewarding LLMs for reasoning that stays coherent and goal-directed, not just for landing the right final answer, makes their reasoning both more …
🎉 Accepted at ICML 2026! Training user simulators to infer what real people believe and feel, not just mimic how they write, produces far more realistic simulated users.
Using LLMs to identify high-quality human annotators by checking if their labels are consistent with AI predictions—helping build better training data while preserving diverse …
ProRefine automatically improves AI prompts during inference by having one AI agent give feedback to refine another agent's prompts—boosting accuracy by 3-37% and helping smaller …
Mixing outputs from multiple LLMs (GPT-4, DeepSeek, etc.) using genetic algorithms to evolve better solutions for complex reasoning tasks—like breeding the best answer from diverse …
Note Presenting at NeurIPS (Math-AI Workshop) Date: December 6, 2025 Time: Sat 3:30 p.m. - 4:15 p.m. Location: NeurIPS 2025 - Workshop Upper Level Ballroom 6A Session Type: Poster …
Asking people to predict how others with different political views would label content reveals hidden biases and improves data quality for content moderation AI.