14 citations · 17 across the 6 of their papers we have counts for
6 papers
JAEGER: Joint 3D Audio-Visual Grounding and Reasoning in Simulated Physical Environments
Zhan Liu, Changli Tang, Yuxin Wang +7
Current audio-visual large language models (AV-LLMs) are predominantly restricted to 2D perception, relying on RGB video and monaural audio. This design choice introduces a fundame…
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, Alexander G. Shaw, Nicholas Carlini +82
AI agents may soon become capable of autonomously completing valuable, long-horizon tasks in diverse domains. Current benchmarks either do not measure real-world tasks, or are not…
Dual Data Scaling for Robust Two-Stage User-Defined Keyword Spotting
Zhiqi Ai, Han Cheng, Yuxin Wang +3
In this paper, we propose DS-KWS, a two-stage framework for robust user-defined keyword spotting. It combines a CTC-based method with a streaming phoneme search module to locate ca…
EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle
Rong Wu, Xiaoman Wang, Jianbiao Mei +8
Current Large Language Model (LLM) agents show strong performance in tool use, but lack the crucial capability to systematically learn from their own experiences. While existing fr…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges
Xinrun Xu, Yuxin Wang, Chaoyi Xu +4
The swift evolution of Large-scale Models (LMs), either language-focused or multi-modal, has garnered extensive attention in both academy and industry. But despite the surge in int…