activity
20212026
most citedReAct: Synergizing Reasoning and Acting in Language Models

596 citations · 1.5k across the 11 of their papers we have counts for

collaborators

12 papers

stat.ML2026

An Efficient Algorithm for Thresholding Monte Carlo Tree Search

Shoma Nameki, Atsuyoshi Nakamura, Junpei Komiyama +1

We introduce the Thresholding Monte Carlo Tree Search problem, in which, given a tree and a threshold , a player must answer whether the root node value of $\mathc…

cs.AI2024

Are LLMs Good Cryptic Crossword Solvers?

Abdelrahman Sadallah, Daria Kotova, Ekaterina Kochmar

Cryptic crosswords are puzzles that rely not only on general knowledge but also on the solver's ability to manipulate language on different levels and deal with various types of wo…

cs.CL2024★ 297 cited

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Petko Georgiev, Ving Ian Lei +1132

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over…

cs.RO2023★ 2 cited

RoboVQA: Multimodal Long-Horizon Reasoning for Robotics

Pierre Sermanet, Tianli Ding, Jeffrey Zhao +18

We present a scalable, bottom-up and intrinsically diverse data collection scheme that can be used for high-level reasoning with long and medium horizons and that has 2.2x higher t…

cs.CL2023★ 574 cited

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Shunyu Yao, Dian Yu, Jeffrey Zhao +4

Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making proce…

cs.AI2022★ 1 cited

Speech Aware Dialog System Technology Challenge (DSTC11)

Hagen Soltau, Izhak Shafran, Mingqiu Wang +6

Most research on task oriented dialog modeling is based on written text input. However, users interact with practical dialog systems often using speech as input. Typically, systems…

cs.CL2022

AnyTOD: A Programmable Task-Oriented Dialog System

Jeffrey Zhao, Yuan Cao, Raghav Gupta +6

We propose AnyTOD, an end-to-end, zero-shot task-oriented dialog (TOD) system capable of handling unseen tasks without task-specific training. We view TOD as a program executed by…

cs.CL2022★ 596 cited

ReAct: Synergizing Reasoning and Acting in Language Models

Shunyu Yao, Jeffrey Zhao, Dian Yu +4

While large language models (LLMs) have demonstrated impressive capabilities across tasks in language understanding and interactive decision making, their abilities for reasoning (…

cs.CL2022★ 6 cited

N-Grammer: Augmenting Transformers with latent n-grams

Aurko Roy, Rohan Anil, Guangda Lai +13

Transformer models have recently emerged as one of the foundational models in natural language processing, and as a byproduct, there is significant recent interest and investment i…

cs.CL2022★ 18 cited

Show, Don't Tell: Demonstrations Outperform Descriptions for Schema-Guided Task-Oriented Dialogue

Raghav Gupta, Harrison Lee, Jeffrey Zhao +3

Building universal dialogue systems that operate across multiple domains/APIs and generalize to new ones with minimal overhead is a critical challenge. Recent works have leveraged…

cs.CL2022★ 33 cited

Description-Driven Task-Oriented Dialog Modeling

Jeffrey Zhao, Raghav Gupta, Yuan Cao +6

Task-oriented dialogue (TOD) systems are required to identify key information from conversations for the completion of given tasks. Such information is conventionally specified in…

cs.CL2021

Effective Sequence-to-Sequence Dialogue State Tracking

Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang +2

Sequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In…