12 citations · 84 across the 24 of their papers we have counts for
8 papers · 1 filter
Dense X Retrieval: What Retrieval Granularity Should We Use?
Tong Chen, Hongwei Wang, Sihao Chen +5
Dense retrieval has become a prominent method to obtain relevant context or world knowledge in open-domain NLP tasks. When we use a learned dense retriever on a retrieval corpus at…
BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
Yifan Jiang, Filip Ilievski, Kaixin Ma +1
The success of language models has inspired the NLP community to attend to tasks that require implicit and complex reasoning, relying on human-like commonsense mechanisms. While su…
Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
Wenhao Yu, Hongming Zhang, Xiaoman Pan +3
Retrieval-augmented language models (RALMs) represent a substantial advancement in the capabilities of large language models, notably in reducing factual hallucination by leveragin…
LASER: LLM Agent with State-Space Exploration for Web Navigation
Kaixin Ma, Hongming Zhang, Hongwei Wang +3
Large language models (LLMs) have been successfully adapted for interactive decision-making tasks like web navigation. While achieving decent performance, previous methods implicit…
A Study of Situational Reasoning for Traffic Understanding
Jiarui Zhang, Filip Ilievski, Kaixin Ma +3
Intelligent Traffic Monitoring (ITMo) technologies hold the potential for improving road safety/security and for enabling smart city infrastructure. Understanding traffic situation…
Chain-of-Skills: A Configurable Model for Open-domain Question Answering
Kaixin Ma, Hao Cheng, Yu Zhang +3
The retrieval model is an indispensable component for real-world knowledge-intensive tasks, e.g., open-domain question answering (ODQA). As separate retrieval skills are annotated…
Knowledge-enhanced Agents for Interactive Text Games
Prateek Chhikara, Jiarui Zhang, Filip Ilievski +2
Communication via natural language is a key aspect of machine intelligence, and it requires computational models to learn and reason about world concepts, with varying levels of su…
Transferring Procedural Knowledge across Commonsense Tasks
Yifan Jiang, Filip Ilievski, Kaixin Ma
Stories about everyday situations are an essential part of human communication, motivating the need to develop AI agents that can reliably understand these stories. Despite the lon…