NLU Workshop Talk: Model-Aided Human Annotation at Scale
AuthorsHadas Kotek
NLU Workshop Talk: Model-Aided Human Annotation at Scale
AuthorsHadas Kotek
On the Effectiveness-Fluency Trade-Off in LLM Conditioning: A Systematic Study
September 30, 2026research area Methods and Algorithms, research area Speech and Natural Language Processingconference EMNLP
Controlling the output of Large Language Models (LLMs) is a central challenge for their reliable deployment, yet a clear understanding of the involved trade-offs remains elusive. Current approaches to conditioning are often evaluated with a narrow focus on their effectiveness at injecting or removing a target concept, neglecting generation quality. We systematically investigate a range of conditioning methods in both injection and removal…
SCLATE: A Substrate for Continual-Learning Agent Training and Evaluation
September 30, 2026research area Methods and Algorithms, research area Tools, Platforms, Frameworks
Continual-learning agents are systems of models, harnesses, and memory operating over long multi-session horizons. Evaluating and training them requires interleaving tasks with agent-side events such as session stop and start, crons, and memory consolidation. Yet existing benchmarks and training frameworks schedule only the benchmark’s own events, leaving each benchmark and agent pair to build a custom scheduling loop. We present SCLATE, an…