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Wenliang Dai

NVIDIA

28 papers hereh-index 2011.4k citations34 works total

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

author position
  • first author9
  • middle author18

Across the 27 of 28 papers where every author was matched, so the position is known.

fields
  • cs.CL22
  • cs.CV4
  • cs.LG1
  • cs.SD1
affiliations
  • NVIDIA
  • HKUST
HomepageORCID 0000-0002-6175-4223
same name
  • Wenliang Dai — 1 paper
  • Wenliang Dai — 1 paper
  • Wenliang Dai — 1 paper

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
20202026
most citedSurvey of Hallucination in Natural Language Generation

4.5k citations · 5.4k across the 26 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…

cs.CV2023

Negative Object Presence Evaluation (NOPE) to Measure Object Hallucination in Vision-Language Models

Holy Lovenia, Wenliang Dai, Samuel Cahyawijaya +2

Object hallucination poses a significant challenge in vision-language (VL) models, often leading to the generation of nonsensical or unfaithful responses with non-existent objects.…

cs.CV2023

Visual Instruction Tuning with Polite Flamingo

Delong Chen, Jianfeng Liu, Wenliang Dai +1

Recent research has demonstrated that the multi-task fine-tuning of multi-modal Large Language Models (LLMs) using an assortment of annotated downstream vision-language datasets si…

cs.CV2023★ 409 cited

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Wenliang Dai, Junnan Li, Dongxu Li +6

Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-lan…

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