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Unsolved research questions waiting for your expertise. Collaborate with the lab, claim a problem, or propose your own. Funding opportunities are attached to select problems.
Develop methods to identify and characterize circuits in models with >100B parameters without prohibitive computational cost.
Design a classifier that detects adversarial prompt injections in real-time with <5ms added latency per request.
Propose and validate human-aligned metrics for scoring poetry, fiction, and visual art generation beyond BLEU/FID.
Apply formal methods to prove properties of reward models used in RLHF, ensuring they preserve human intent under distribution shift.
Extend activation patching techniques to MoE models where expert routing introduces non-trivial causal structure.
Measure how biases in high-resource training languages transfer to low-resource language outputs during multilingual fine-tuning.
Achieve competitive accuracy with 10x reduction in FLOPs for on-device inference through novel quantization and pruning strategies.
Build a system that discovers new adversarial attack categories autonomously, beyond known jailbreak taxonomies.
Extend fairness metrics to handle intersectional protected groups without exponential sample size requirements.
Prove convergence bounds for asynchronous distributed training with heterogeneous hardware and variable network latency.
Submit your open problem to the board. If accepted, it becomes visible to the entire research community and may qualify for lab funding.
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