11 citations · 18 across the 23 of their papers we have counts for
7 papers · 1 filter
SongCraft: Unified Song Generation and Editing with Reconstructive Learning
Haohe Liu, Varun Nagaraja, Gael Le Lan +5
Song generation and editing have mostly been treated as separate tasks. Existing editing methods often require noise injection and regeneration or curated paired training data. We…
Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls
Guoyao Yu, Xiaoqing Sun, Ziqi Huang +13
Large language model agents derive much of their capability from tool use. Existing research on tool use has largely focused on selecting the right tool and orchestrating the order…
VLM3: Vision Language Models Are Native 3D Learners
Zhipeng Cai, Zhuang Liu, Yunyang Xiong +3
Vision Language Models (VLMs) enable a unified model to solve various vision tasks through prompting. They have shown promising performance in semantic understanding. However, 3D u…
Exploring Audio Hallucination in Egocentric Video Understanding
Ashish Seth, Xinhao Mei, Changsheng Zhao +9
Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly when visual information is unstab…
Neural Computers
Mingchen Zhuge, Changsheng Zhao, Haozhe Liu +16
We propose a new frontier: Neural Computers (NCs) that unify computation, memory, and I/O of traditional computers in a learned runtime state. Our long-term goal is the Completely…
EgoAVU: Egocentric Audio-Visual Understanding
Ashish Seth, Xinhao Mei, Changsheng Zhao +9
Understanding egocentric videos plays a vital role for embodied intelligence. Recent multi-modal large language models (MLLMs) can accept both visual and audio inputs. However, due…
SLAP: Scalable Language-Audio Pretraining with Variable-Duration Audio and Multi-Objective Training
Xinhao Mei, Gael Le Lan, Haohe Liu +5
Contrastive language-audio pretraining (CLAP) has achieved notable success in learning semantically rich audio representations and is widely adopted for various audio-related tasks…