As LLMs become increasingly powerful, one key question becomes more urgent: How can we make their behavior more controllable and predictable?
Traditional approaches such as retraining or fine-tuning can be costly. Steering offers another path: instead of updating the whole
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- "After evaluating 300 agent tasks, we revisited two fundamental questions: what should we evaluate, and how can we make the evaluation trustworthy?" NICE Talk NO.176 We invite Bowen Ye, PhD student at Peking University, to introduce Claw-Eval, an end-to-end evaluation framework
- NICE Talk NO.175 invites the Guanlin Dong to share a new paradigm for general agent training: environment-agent co-evolution. Paper: Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence arXiv: arxiv.org/pdf/2604.18292 Project website:
- NICE Talk 173 invites🎙️Heyuan Huang (Algorithm Engineer from OPPO Research Institute) to share the design and vision of TopoClaw. Talk Time ⏰ EST: 5.16 22:00~23:00 😊 Register on Luma: luma.com/bdo4kcmp 📌 Watch live on YouTube:youtube.com/watch?v=qFyGHP… 💻 With the rapid
- NICE Talk 172 invites🎙️Bingxiang He @HBX_hbx, PhD student at Tsinghua University @TsinghuaNLP, to share Three Frontiers of Scalable RL for LLMs. Talk Time ⏰ EST: 5.15 22:00~23:00 📌 Watch live on YouTube: youtube.com/live/KOs6wqNu8… 😊 Register: luma.com/ymaa3poa 🤠Can RL

