Lawrence Phillips

26 papers B 3Journal 18Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Automating Forecasting Question Generation and Resolution for AI Evaluation. CoRR Nikos I. Bosse, Peter Mühlbacher, Jack Wildman, Lawrence Phillips, Dan Schwarz
2026	J	`jnl`	MechPert: Mechanistic Consensus as an Inductive Bias for Unseen Perturbation Prediction. CoRR Marc Boubnovski Martell, Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra, Robert Kitchen, Jesper Ferkinghoff-Borg, Jialin Yu, Philip Torr, Kaspar Märtens
2025	J	`jnl`	Bench to the Future: A Pastcasting Benchmark for Forecasting Agents. CoRR Jack Wildman, Nikos I. Bosse, Daniel Hnyk, Peter Mühlbacher, Finn Hambly, Jon Evans, Dan Schwarz, Lawrence Phillips
2025	—	`conf`	CellRep: A Multichannel Image Representation Learning Model. CVPR Workshops Lawrence Phillips, Rory M. Donovan-Maiye
2025	J	`jnl`	Deep Research Bench: Evaluating AI Web Research Agents. CoRR Nikos I. Bosse, Jon Evans, Robert G. Gambee, Daniel Hnyk, Peter Mühlbacher, Lawrence Phillips, Dan Schwarz, Jack Wildman
2025	J	`jnl`	Query, Don't Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries. CoRR Josefa Lia Stoisser, Marc Boubnovski Martell, Kaspar Märtens, Lawrence Phillips, Stephen Michael Town, Rory M. Donovan-Maiye, Julien Fauqueur
2025	J	`jnl`	STRuCT-LLM: Unifying Tabular and Graph Reasoning with Reinforcement Learning for Semantic Parsing. CoRR Josefa Lia Stoisser, Marc Boubnovski Martell, Lawrence Phillips, Casper Hansen, Julien Fauqueur
2025	J	`jnl`	SynthPert: Enhancing LLM Biological Reasoning via Synthetic Reasoning Traces for Cellular Perturbation Prediction. CoRR Lawrence Phillips, Marc Boubnovski Martell, Aditya Misra, Josefa Lia Stoisser, Cesar A. Prada-Medina, Rory M. Donovan-Maiye, Kaspar Märtens
2025	J	`jnl`	Towards Agents That Know When They Don't Know: Uncertainty as a Control Signal for Structured Reasoning. CoRR Josefa Lia Stoisser, Marc Boubnovski Martell, Lawrence Phillips, Gianluca Mazzoni, Lea Mørch Harder, Philip Torr, Jesper Ferkinghoff-Borg, Kaspar Märtens, Julien Fauqueur
2025	J	`jnl`	Towards Label-Free Biological Reasoning Synthetic Dataset Creation via Uncertainty Filtering. CoRR Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra, Tom A. Lamb, Philip Torr, Marc Boubnovski Martell, Julien Fauqueur, Kaspar Märtens
2024	J	`jnl`	Towards a Realistic Long-Term Benchmark for Open-Web Research Agents. CoRR Peter Mühlbacher, Nikos I. Bosse, Lawrence Phillips
2021	J	`jnl`	Intrinsic uncertainties and where to find them. CoRR Francesco Farina, Lawrence Phillips, Nicola J. Richmond
2019	J	`jnl`	Explanatory Masks for Neural Network Interpretability. CoRR Lawrence Phillips, Garrett B. Goh, Nathan O. Hodas
2019	J	`jnl`	Metric-Based Few-Shot Learning for Video Action Recognition. CoRR Chris Careaga, Brian Hutchinson, Nathan Oken Hodas, Lawrence Phillips
2019	J	`jnl`	Sparse hierarchical representation learning on molecular graphs. CoRR Matthias Bal, Hagen Triendl, Mariana Assmann, Michael Craig, Lawrence Phillips, Jarvist Moore Frost, Usman Bashir, Noor Shaker, Vid Stojevic
2018	J	`jnl`	Few-Shot Learning with Metric-Agnostic Conditional Embeddings. CoRR Nathan Hilliard, Lawrence Phillips, Scott Howland, Artëm Yankov, Courtney D. Corley, Nathan O. Hodas
2018	—	`conf`	Predicting Foreign Language Usage from English-Only Social Media Posts. NAACL-HLT (2) Svitlana Volkova, Stephen Ranshous, Lawrence Phillips
2017	B	`conf`	Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks. CogSci Lawrence Phillips, Nathan Oken Hodas
2017	J	`jnl`	Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks. CoRR Lawrence Phillips, Nathan Oken Hodas
2017	—	`conf`	Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams. Rep4NLP@ACL Lawrence Phillips, Kyle Shaffer, Dustin Arendt, Nathan Oken Hodas, Svitlana Volkova
2017	J	`jnl`	Using Social Media to Predict the Future: A Systematic Literature Review. CoRR Lawrence Phillips, Chase Dowling, Kyle Shaffer, Nathan Oken Hodas, Svitlana Volkova
2015	—	`—`	The Role of Empirical Evidence in Modeling Speech Segmentation. Lawrence Phillips
2015	J	`jnl`	The Utility of Cognitive Plausibility in Language Acquisition Modeling: Evidence From Word Segmentation. Cogn. Sci. Lawrence Phillips, Lisa Pearl
2015	—	`conf`	Utility-based evaluation metrics for models of language acquisition: A look at speech segmentation. CMCL@NAACL-HLT Lawrence Phillips, Lisa Pearl
2014	B	`conf`	Bayesian inference as a viable cross-linguistic word segmentation strategy: It's all about what's useful. CogSci Lawrence Phillips, Lisa Pearl
2012	B	`conf`	"Less is More" in Bayesian Word Segmentation: When cognitively plausible learners outperform the ideal. CogSci Lawrence Phillips, Lisa Pearl