209 citations · 646 across the 46 of their papers we have counts for
53 papers
CT: Counterfactual Causal Reasoning for Sentiment Shifts in Social-Media Conversation Trees
S M Rafiuddin, Atriya Sen
Sentiment in social-media threads does not only vary across posts; it shifts as users react to claims, corrections, evidence, and hostility within a branching reply tree. We study…
Human detectors are surprisingly powerful reward models
Kumar Ashutosh, XuDong Wang, Xi Yin +4
Video generation models have recently achieved impressive visual fidelity and temporal coherence. Yet, they continue to struggle with complex, non-rigid motions, especially when sy…
Toward Diffusible High-Dimensional Latent Spaces: A Frequency Perspective
Bolin Lai, Xudong Wang, Saketh Rambhatla +4
Latent diffusion has become the default paradigm for visual generation, yet we observe a persistent reconstruction-generation trade-off as latent dimensionality increases: higher-c…
From KMMLU-Redux to KMMLU-Pro: A Professional Korean Benchmark Suite for LLM Evaluation
Seokhee Hong, Sunkyoung Kim, Guijin Son +3
The development of Large Language Models (LLMs) requires robust benchmarks that encompass not only academic domains but also industrial fields to effectively evaluate their applica…
Balancing Knowledge Delivery and Emotional Comfort in Healthcare Conversational Systems
Shang-Chi Tsai, Yun-Nung Chen
With the advancement of large language models, many dialogue systems are now capable of providing reasonable and informative responses to patients' medical conditions. However, whe…
Dialect Normalization using Large Language Models and Morphological Rules
Antonios Dimakis, John Pavlopoulos, Antonios Anastasopoulos
Natural language understanding systems struggle with low-resource languages, including many dialects of high-resource ones. Dialect-to-standard normalization attempts to tackle thi…
Jailbreak Distillation: Renewable Safety Benchmarking
Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5
Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…
ZeroSumEval: An Extensible Framework For Scaling LLM Evaluation with Inter-Model Competition
Hisham A. Alyahya, Haidar Khan, Yazeed Alnumay +2
We introduce ZeroSumEval, a dynamic, competition-based, and evolving evaluation framework for Large Language Models (LLMs) that leverages competitive games. ZeroSumEval encompasses…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
Diffusion Autoencoders are Scalable Image Tokenizers
Yinbo Chen, Rohit Girdhar, Xiaolong Wang +2
Tokenizing images into compact visual representations is a key step in learning efficient and high-quality image generative models. We present a simple diffusion tokenizer (DiTo) t…
LLMs can see and hear without any training
Kumar Ashutosh, Yossi Gandelsman, Xinlei Chen +2
We present MILS: Multimodal Iterative LLM Solver, a surprisingly simple, training-free approach, to imbue multimodal capabilities into your favorite LLM. Leveraging their innate ab…
MotiF: Making Text Count in Image Animation with Motion Focal Loss
Shijie Wang, Samaneh Azadi, Rohit Girdhar +3
Text-Image-to-Video (TI2V) generation aims to generate a video from an image following a text description, which is also referred to as text-guided image animation. Most existing m…
LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch
Jan Pfister, Julia Wunderle, Andreas Hotho
We create two German-only decoder models, LLäMmlein 120M and 1B, transparently from scratch and publish them, along with the training data, for the German NLP research community to…
Human Action Anticipation: A Survey
Bolin Lai, Sam Toyer, Tushar Nagarajan +7
Predicting future human behavior is an increasingly popular topic in computer vision, driven by the interest in applications such as autonomous vehicles, digital assistants and hum…
Movie Gen: A Cast of Media Foundation Models
Adam Polyak, Amit Zohar, Andrew Brown +85
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabili…
The Llama 3 Herd of Models
Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri +556
Modern artificial intelligence (AI) systems are powered by foundation models. This paper presents a new set of foundation models, called Llama 3. It is a herd of language models th…
SoundingActions: Learning How Actions Sound from Narrated Egocentric Videos
Changan Chen, Kumar Ashutosh, Rohit Girdhar +2
We propose a novel self-supervised embedding to learn how actions sound from narrated in-the-wild egocentric videos. Whereas existing methods rely on curated data with known audio-…
InstanceDiffusion: Instance-level Control for Image Generation
Xudong Wang, Trevor Darrell, Sai Saketh Rambhatla +2
Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instanc…
Generating Illustrated Instructions
Sachit Menon, Ishan Misra, Rohit Girdhar
We introduce the new task of generating Illustrated Instructions, i.e., visual instructions customized to a user's needs. We identify desiderata unique to this task, and formalize…
Motion-Conditioned Image Animation for Video Editing
Wilson Yan, Andrew Brown, Pieter Abbeel +2
We introduce MoCA, a Motion-Conditioned Image Animation approach for video editing. It leverages a simple decomposition of the video editing problem into image editing followed by…
Emu Video: Factorizing Text-to-Video Generation by Explicit Image Conditioning
Rohit Girdhar, Mannat Singh, Andrew Brown +7
We present Emu Video, a text-to-video generation model that factorizes the generation into two steps: first generating an image conditioned on the text, and then generating a video…
VideoCutLER: Surprisingly Simple Unsupervised Video Instance Segmentation
Xudong Wang, Ishan Misra, Ziyun Zeng +2
Existing approaches to unsupervised video instance segmentation typically rely on motion estimates and experience difficulties tracking small or divergent motions. We present Video…
ImageBind: One Embedding Space To Bind Them All
Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu +4
We present ImageBind, an approach to learn a joint embedding across six different modalities - images, text, audio, depth, thermal, and IMU data. We show that all combinations of p…
The effectiveness of MAE pre-pretraining for billion-scale pretraining
Mannat Singh, Quentin Duval, Kalyan Vasudev Alwala +9
This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recognition tasks. Typically, state-of-the-art foundation models are pretrained…