90 citations · 427 across the 29 of their papers we have counts for
8 papers · 1 filter
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking
Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal +9
Reward models play a key role in aligning language model applications towards human preferences. However, this setup creates an incentive for the language model to exploit errors i…
SEMQA: Semi-Extractive Multi-Source Question Answering
Tal Schuster, Adam D. Lelkes, Haitian Sun +4
Recently proposed long-form question answering (QA) systems, supported by large language models (LLMs), have shown promising capabilities. Yet, attributing and verifying their gene…
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors
Ido Amos, Jonathan Berant, Ankit Gupta
Modeling long-range dependencies across sequences is a longstanding goal in machine learning and has led to architectures, such as state space models, that dramatically outperform…
Making Retrieval-Augmented Language Models Robust to Irrelevant Context
Ori Yoran, Tomer Wolfson, Ori Ram +1
Retrieval-augmented language models (RALMs) hold promise to produce language understanding systems that are are factual, efficient, and up-to-date. An important desideratum of RALM…
Retrieval-Pretrained Transformer: Long-range Language Modeling with Self-retrieval
Ohad Rubin, Jonathan Berant
Retrieval-augmented language models (LMs) have received much attention recently. However, typically the retriever is not trained jointly as a native component of the LM, but added…
From Pixels to UI Actions: Learning to Follow Instructions via Graphical User Interfaces
Peter Shaw, Mandar Joshi, James Cohan +6
Much of the previous work towards digital agents for graphical user interfaces (GUIs) has relied on text-based representations (derived from HTML or other structured data sources),…