When One LLM Drools, Multi-LLM Collaboration Rules

S Feng, W Ding, A Liu, Z Wang, W Shi, Y Wang… - arxiv preprint arxiv …, 2025 - arxiv.org
This position paper argues that in many realistic (ie, complex, contextualized, subjective)
scenarios, one LLM is not enough to produce a reliable output. We challenge the status quo …

Jackpot! Alignment as a Maximal Lottery

RR Maura-Rivero, M Lanctot, F Visin… - arxiv preprint arxiv …, 2025 - arxiv.org
Reinforcement Learning from Human Feedback (RLHF), the standard for aligning Large
Language Models (LLMs) with human values, is known to fail to satisfy properties that are …

Context is Key in Agent Security

L Tsai, E Bagdasarian - arxiv preprint arxiv:2501.17070, 2025 - arxiv.org
Judging the safety of an action, whether taken by a human or a system, must take into
account the context in which the action takes place. Deleting an email from user's mailbox …