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Jiaya Jia

18 papers hereh-index 11431 citations23 works total

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

author position
  • middle author1
  • last author15

Across the 16 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.LG4
  • cs.RO4
  • cs.CL2
  • cs.AI1
same name
  • Jiaya Jia — 115 papers, h 107
  • Jiaya Jia — 28 papers, h 15
  • Jiaya Jia — 12 papers, h 5
  • Jiaya Jia — 11 papers, h 4
  • Jiaya Jia — 9 papers, h 5
  • Jiaya Jia — 2 papers

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
20232026
most citedLISA++: An Improved Baseline for Reasoning Segmentation with Large Language Model

4 citations · 8 across the 16 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2025

DynamicBench: Evaluating Real-Time Report Generation in Large Language Models

Jingyao Li, Hao Sun, Zile Qiao +5

Traditional benchmarks for large language models (LLMs) typically rely on static evaluations through storytelling or opinion expression, which fail to capture the dynamic requireme…

cs.LG2024

QuickLLaMA: Query-aware Inference Acceleration for Large Language Models

Jingyao Li, Han Shi, Xin Jiang +3

The capacity of Large Language Models (LLMs) to comprehend and reason over long contexts is pivotal for advancements in diverse fields. Yet, they still stuggle with capturing long-…

cs.LG2023

BAL: Balancing Diversity and Novelty for Active Learning

Jingyao Li, Pengguang Chen, Shaozuo Yu +2

The objective of Active Learning is to strategically label a subset of the dataset to maximize performance within a predetermined labeling budget. In this study, we harness feature…

cs.LG2023

MoTCoder: Elevating Large Language Models with Modular of Thought for Challenging Programming Tasks

Jingyao Li, Pengguang Chen, Bin Xia +2

Large Language Models (LLMs) have showcased impressive capabilities in handling straightforward programming tasks. However, their performance tends to falter when confronted with m…

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