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20232026
most citedScaling Up LLM Reviews for Google Ads Content Moderation

13 citations · 52 across the 48 of their papers we have counts for

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Showing 2024Show all

15 papers · 1 filter

cs.CV2024

Negative Token Merging: Image-based Adversarial Feature Guidance

Jaskirat Singh, Lindsey Li, Weijia Shi +7

Text-based adversarial guidance using a negative prompt has emerged as a widely adopted approach to steer diffusion models away from producing undesired concepts. While useful, per…

cs.RO2024

The One RING: a Robotic Indoor Navigation Generalist

Ainaz Eftekhar, Rose Hendrix, Luca Weihs +11

Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-s…

cs.CV2024

ActionAtlas: A VideoQA Benchmark for Domain-specialized Action Recognition

Mohammadreza Salehi, Jae Sung Park, Tanush Yadav +5

Our world is full of varied actions and moves across specialized domains that we, as humans, strive to identify and understand. Within any single domain, actions can often appear q…

cs.CV2024

One Diffusion to Generate Them All

Duong H. Le, Tuan Pham, Sangho Lee +5

We introduce OneDiffusion, a versatile, large-scale diffusion model that seamlessly supports bidirectional image synthesis and understanding across diverse tasks. It enables condit…

cs.RO2024★ 4 cited

AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation

Jiafei Duan, Wilbert Pumacay, Nishanth Kumar +7

Robotic manipulation in open-world settings requires not only task execution but also the ability to detect and learn from failures. While recent advances in vision-language models…

cs.RO2024★ 2 cited

RoboPoint: A Vision-Language Model for Spatial Affordance Prediction for Robotics

Wentao Yuan, Jiafei Duan, Valts Blukis +5

From rearranging objects on a table to putting groceries into shelves, robots must plan precise action points to perform tasks accurately and reliably. In spite of the recent adopt…

cs.RO2024★ 5 cited

Manipulate-Anything: Automating Real-World Robots using Vision-Language Models

Jiafei Duan, Wentao Yuan, Wilbert Pumacay +4

Large-scale endeavors like and widespread community efforts such as Open-X-Embodiment have contributed to growing the scale of robot demonstration data. However, there is still an…

cs.CV2024

Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models

Yushi Hu, Weijia Shi, Xingyu Fu +5

Humans draw to facilitate reasoning: we draw auxiliary lines when solving geometry problems; we mark and circle when reasoning on maps; we use sketches to amplify our ideas and rel…

cs.CL2024★ 1 cited

Superposed Decoding: Multiple Generations from a Single Autoregressive Inference Pass

Ethan Shen, Alan Fan, Sarah M. Pratt +7

Many applications today provide users with multiple auto-complete drafts as they type, including GitHub's code completion, Gmail's smart compose, and Apple's messaging auto-suggest…

cs.CV2024

ImageInWords: Unlocking Hyper-Detailed Image Descriptions

Roopal Garg, Andrea Burns, Burcu Karagol Ayan +7

Despite the longstanding adage "an image is worth a thousand words," generating accurate hyper-detailed image descriptions remains unsolved. Trained on short web-scraped image text…

cs.CV2024★ 1 cited

BLINK: Multimodal Large Language Models Can See but Not Perceive

Xingyu Fu, Yushi Hu, Bangzheng Li +7

We introduce Blink, a new benchmark for multimodal language models (LLMs) that focuses on core visual perception abilities not found in other evaluations. Most of the Blink tasks c…

cs.HC2024

EVE: Enabling Anyone to Train Robots using Augmented Reality

Jun Wang, Chun-Cheng Chang, Jiafei Duan +2

The increasing affordability of robot hardware is accelerating the integration of robots into everyday activities. However, training a robot to automate a task requires expensive t…

cs.CV2024★ 1 cited

Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use

Imad Eddine Toubal, Aditya Avinash, Neil Gordon Alldrin +10

From content moderation to wildlife conservation, the number of applications that require models to recognize nuanced or subjective visual concepts is growing. Traditionally, devel…

cs.IR2024★ 13 cited

Scaling Up LLM Reviews for Google Ads Content Moderation

Wei Qiao, Tushar Dogra, Otilia Stretcu +11

Large language models (LLMs) are powerful tools for content moderation, but their inference costs and latency make them prohibitive for casual use on large datasets, such as the Go…

cs.RO2024★ 1 cited

THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation

Wilbert Pumacay, Ishika Singh, Jiafei Duan +3

To realize effective large-scale, real-world robotic applications, we must evaluate how well our robot policies adapt to changes in environmental conditions. Unfortunately, a major…