Christopher Potts
- Papers
- 37
Cite
Notes
Only stored in your browser.
Authored papers
37HyperSteer: Activation Steering at Scale with Hypernetworks
arXiv 2025
WARP: An Efficient Engine for Multi-Vector Retrieval
arXiv 2025
Do Language Models Use Their Depth Efficiently?
arXiv 2025
Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors
arXiv 2025
Structured Prompting Enables More Robust Evaluation of Language Models
arXiv 2025
GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning
arXiv 2025
Multi-module GRPO: Composing Policy Gradients and Prompt Optimization for Language Model Programs
arXiv 2025
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
arXiv 2024
CausalGym: Benchmarking causal interpretability methods on linguistic tasks
arXiv 2024
ReFT: Representation Finetuning for Language Models
arXiv 2024
Improving Pretraining Data Using Perplexity Correlations
arXiv 2024
Recurrent Neural Networks Learn to Store and Generate Sequences using Non-Linear Representations
arXiv 2024
Building Efficient and Effective OpenQA Systems for Low-Resource Languages
arXiv 2024
A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments
arXiv 2024
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
arXiv 2024
In-Context Learning for Extreme Multi-Label Classification
arXiv 2024
MoEUT: Mixture-of-Experts Universal Transformers
arXiv 2024
RAVEL: Evaluating Interpretability Methods on Disentangling Language Model Representations
arXiv 2024
Mission: Impossible Language Models
arXiv 2024
MrT5: Dynamic Token Merging for Efficient Byte-level Language Models
arXiv 2024
I am a Strange Dataset: Metalinguistic Tests for Language Models
arXiv 2024
UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers
arXiv 2023
GIO: Gradient Information Optimization for Training Dataset Selection
arXiv 2023
ContextRef: Evaluating Referenceless Metrics For Image Description Generation
arXiv 2023
ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning
arXiv 2023
ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
arXiv 2023
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop Questions
arXiv 2023
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
TMLR
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
arXiv 2022
PLAID: An Efficient Engine for Late Interaction Retrieval
arXiv 2022
Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models
arXiv 2022
Causal Proxy Models for Concept-Based Model Explanations
arXiv 2022
Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics
arXiv 2022
Data and Representation for Turkish Natural Language Inference
EMNLP 2020 11
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation
EMNLP (BlackboxNLP) 2020 11
DynaSent: A Dynamic Benchmark for Sentiment Analysis
ACL 2021 5
A large annotated corpus for learning natural language inference
a-large-annotated-corpus-for-learning-natural-1
Affiliations
Frequent co-authors
10from 37 papers
Atticus Geiger
Christopher D. Manning
Omar Khattab
Zhengxuan Wu
Matei Zaharia
founder
Aryaman Arora
Jing Huang
Karel D'Oosterlinck
Róbert Csordás
Dilara Soylu
grad-student