most citedAugmenting Language Models with Long-Term Memory

33 citations · 52 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV202313 cited

GPT-4V(ision) as a Generalist Evaluator for Vision-Language Tasks

Xinlu Zhang, Yujie Lu, Weizhi Wang +7

Automatically evaluating vision-language tasks is challenging, especially when it comes to reflecting human judgments due to limitations in accounting for fine-grained details. Alt…

cs.CL20232 cited

Evaluating the Instruction-Following Robustness of Large Language Models to Prompt Injection

Zekun Li, Baolin Peng, Pengcheng He +1

Large Language Models (LLMs) have demonstrated exceptional proficiency in instruction-following, becoming increasingly crucial across various applications. However, this capability…

cs.CL202333 cited

Augmenting Language Models with Long-Term Memory

Weizhi Wang, Li Dong, Hao Cheng +4

Existing large language models (LLMs) can only afford fix-sized inputs due to the input length limit, preventing them from utilizing rich long-context information from past inputs.…

cs.CL2023

STEPS: A Benchmark for Order Reasoning in Sequential Tasks

Weizhi Wang, Hong Wang, Xifeng Yan

Various human activities can be abstracted into a sequence of actions in natural text, i.e. cooking, repairing, manufacturing, etc. Such action sequences heavily depend on the exec…

cs.CL2023

Graph Reasoning for Question Answering with Triplet Retrieval

Shiyang Li, Yifan Gao, Haoming Jiang +5

Answering complex questions often requires reasoning over knowledge graphs (KGs). State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which ar…

cs.CL2023

Language Model Detoxification in Dialogue with Contextualized Stance Control

Jing Qian, Xifeng Yan

To reduce the toxic degeneration in a pretrained Language Model (LM), previous work on Language Model detoxification has focused on reducing the toxicity of the generation itself (…