3 papers
cs.CL2026
Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging
Jinglan Gong, Jiefan Lu, Hewei Guo +5
Evaluating large language models (LLMs) as multi-turn conversational partners requires probing capabilities that single-turn benchmarks miss: persona consistency, evolving intent t…
cs.CV2026
SenseNova-MARS: Empowering Multimodal Agentic Reasoning and Search via Reinforcement Learning
Yong Xien Chng, Tao Hu, Wenwen Tong +10
While Vision-Language Models (VLMs) can solve complex tasks through agentic reasoning, their capabilities remain largely constrained to text-oriented chain-of-thought or isolated t…
cs.CV2025
InteractiveOmni: A Unified Omni-modal Model for Audio-Visual Multi-turn Dialogue
Wenwen Tong, Hewei Guo, Dongchuan Ran +23
We introduce InteractiveOmni, a unified and open-source omni-modal large language model for audio-visual multi-turn interaction, ranging from 4B to 8B parameters, designed to lead…