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Jing Li

6 papers hereh-index 7164 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author6

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.AI2
  • cs.LG1
same name
  • Jing Li — 17 papers, h 30
  • Jing Li — 14 papers, h 17
  • Jing Li — 14 papers, h 5
  • Jing Li — 14 papers, h 6
  • Jing Li — 12 papers, h 16
  • Jing Li — 10 papers, h 43

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedA Survey of Machine Narrative Reading Comprehension Assessments

5 citations · 9 across the 5 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

PRELUDE: A Benchmark Designed to Require Global Comprehension and Reasoning over Long Contexts

Mo Yu, Tsz Ting Chung, Chulun Zhou +8

We introduce PRELUDE, a benchmark for evaluating long-context understanding through the task of determining whether a character's prequel story is consistent with the canonical nar…

cs.CL2024

MANGO: A Benchmark for Evaluating Mapping and Navigation Abilities of Large Language Models

Peng Ding, Jiading Fang, Peng Li +6

Large language models such as ChatGPT and GPT-4 have recently achieved astonishing performance on a variety of natural language processing tasks. In this paper, we propose MANGO, a…

cs.CL2023

Can Large Language Models Play Text Games Well? Current State-of-the-Art and Open Questions

Chen Feng Tsai, Xiaochen Zhou, Sierra S. Liu +3

Large language models (LLMs) such as ChatGPT and GPT-4 have recently demonstrated their remarkable abilities of communicating with human users. In this technical report, we take an…

cs.CL2022

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

Yisi Sang, Xiangyang Mou, Mo Yu +3

We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.