Zhi-Hong Deng

EMO: A Closed-Loop Test-Time Computation Framework via Alternating Context Optimization and Logits Steering

Test-time context optimization adapts frozen language models through textual feedback, but ordinary conditional generation provides no separate control over how strongly to reinforce the distributional changes induced by a context update. We introduce EMO, a training-free framework inspired by expectation--maximization...