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Hao Cheng

41 papers hereh-index 396.1k citations308 works total

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

author position
  • first author17
  • middle author22

Across the 39 of 41 papers where every author was matched, so the position is known.

fields
  • cs.CV17
  • cs.LG9
  • cs.CL4
  • cs.RO4
  • cs.CR2
  • cs.DC1
same name
  • Hao Cheng — 44 papers, h 27
  • Hao Cheng — 22 papers, h 8
  • Hao Cheng — 10 papers, h 8
  • Hao Cheng — 7 papers, h 6
  • Hao Cheng — 6 papers, h 7
  • Hao Cheng — 6 papers, h 2

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
20192023
most citedLearning with Noisy Labels Revisited: A Study Using Real-World Human Annotations

62 citations · 250 across the 38 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.RO2022

GATraj: A Graph- and Attention-based Multi-Agent Trajectory Prediction Model

Hao Cheng, Mengmeng Liu, Lin Chen +3

Trajectory prediction has been a long-standing problem in intelligent systems like autonomous driving and robot navigation. Models trained on large-scale benchmarks have made signi…

cs.CL2022★ 6 cited

INSCIT: Information-Seeking Conversations with Mixed-Initiative Interactions

Zeqiu Wu, Ryu Parish, Hao Cheng +4

In an information-seeking conversation, a user may ask questions that are under-specified or unanswerable. An ideal agent would interact by initiating different response types acco…

cs.CV2022

READ: Aggregating Reconstruction Error into Out-of-distribution Detection

Wenyu Jiang, Yuxin Ge, Hao Cheng +3

Detecting out-of-distribution (OOD) samples is crucial to the safe deployment of a classifier in the real world. However, deep neural networks are known to be overconfident for abn…

cs.LG2022★ 6 cited

Identifiability of Label Noise Transition Matrix

Yang Liu, Hao Cheng, Kun Zhang

The noise transition matrix plays a central role in the problem of learning with noisy labels. Among many other reasons, a large number of existing solutions rely on access to it.…

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