301 citations · 373 across the 15 of their papers we have counts for
16 papers
Rationalizing Boltzmann Rationality: An Axiomatic Characterization of Entropy-Regularized Policies
Silviu Pitis
The softmax policy is the default model of stochastic choice in reinforcement learning (RL). Various justifications based on robustness, explora…
Simulating Viva Voce Examinations to Evaluate Clinical Reasoning in Large Language Models
Christopher Chiu, Silviu Pitis, Mihaela van der Schaar
Clinical reasoning in medicine is a hypothesis-driven process where physicians refine diagnoses from limited information through targeted history, physical examination, and diagnos…
Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries
Blair Yang, Fuyang Cui, Keiran Paster +4
The rapid development and dynamic nature of large language models (LLMs) make it difficult for conventional quantitative benchmarks to accurately assess their capabilities. We prop…
Improving Context-Aware Preference Modeling for Language Models
Silviu Pitis, Ziang Xiao, Nicolas Le Roux +1
While finetuning language models from pairwise preferences has proven remarkably effective, the underspecified nature of natural language presents critical challenges. Direct prefe…
Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards
Silviu Pitis
As the capabilities of artificial agents improve, they are being increasingly deployed to service multiple diverse objectives and stakeholders. However, the composition of these ob…
Identifying the Risks of LM Agents with an LM-Emulated Sandbox
Yangjun Ruan, Honghua Dong, Andrew Wang +6
Recent advances in Language Model (LM) agents and tool use, exemplified by applications like ChatGPT Plugins, enable a rich set of capabilities but also amplify potential risks - s…