4 citations · 6 across the 14 of their papers we have counts for
5 papers · 1 filter
Relational Composition in Neural Networks: A Survey and Call to Action
Martin Wattenberg, Fernanda B. Viégas
Many neural nets appear to represent data as linear combinations of "feature vectors." Algorithms for discovering these vectors have seen impressive recent success. However, we arg…
Dialogue Action Tokens: Steering Language Models in Goal-Directed Dialogue with a Multi-Turn Planner
Kenneth Li, Yiming Wang, Fernanda Viégas +1
We present an approach called Dialogue Action Tokens (DAT) that adapts language model agents to plan goal-directed dialogues. The core idea is to treat each utterance as an action,…
Designing a Dashboard for Transparency and Control of Conversational AI
Yida Chen, Aoyu Wu, Trevor DePodesta +9
Conversational LLMs function as black box systems, leaving users guessing about why they see the output they do. This lack of transparency is potentially problematic, especially gi…
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
Kenneth Li, Samy Jelassi, Hugh Zhang +3
We present an approach called Q-probing to adapt a pre-trained language model to maximize a task-specific reward function. At a high level, Q-probing sits between heavier approache…
Measuring and Controlling Instruction (In)Stability in Language Model Dialogs
Kenneth Li, Tianle Liu, Naomi Bashkansky +4
System-prompting is a standard tool for customizing language-model chatbots, enabling them to follow a specific instruction. An implicit assumption in the use of system prompts is…