1 citations · 1 across the 11 of their papers we have counts for
13 papers
Aspects of SUSY gauge theories and applications to Quantum Field Theory and Gravity
Andrea Cipriani
This thesis investigates the application of techniques developed in supersymmetric gauge theories to physical problems in Quantum Field Theory and Gravity, focusing on the Seiberg-…
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…
Omni-Perception Policy Optimization for Multimodal Emotion Reasoning
Zhiyuan Han, Beier Zhu, Wenwen Tong +6
We find that current emotion-oriented Omni-MLLMs still lack reliable omni-modal perception: they (i) underutilize multimodal cues in their reasoning trajectories and (ii) exhibit u…
MER-R1: Multimodal Emotion Reasoning via Slow-Fast Thinking Synergy
Zhiyuan Han, Beier Zhu, Wenwen Tong +8
We find that explicit reasoning does not necessarily translate into better multimodal emotion recognition (MER) accuracy, even though it makes predictions more interpretable. Speci…
From Pixels to Words -- Towards Native One-Vision Models at Scale
Haiwen Diao, Jiahao Wang, Penghao Wu +18
Current vision-language models (VLMs) typically stitch together separate image encoders and language decoders via multi-stage alignment, a modular framework that inevitably fragmen…
SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture
Haiwen Diao, Penghao Wu, Hanming Deng +55
Recent large vision-language models (VLMs) remain fundamentally constrained by a persistent dichotomy: understanding and generation are treated as distinct problems, leading to fra…
EgoPro-Bench: Benchmarking Personalized Proactive Interaction in Egocentric Video Streams
Dongchuan Ran, Linyu Ou, Xueheng Li +5
Existing Multimodal Large Language Models (MLLMs) remain primarily reactive, failing to continuously perceive environments or proactively assist users. While emerging benchmarks ad…
Kirchhoff index of a nested geometric graph with weighted multiple edges
Da-yeon Huh
Kirchhoff index, Kf(G), introduced by Klein and Randic in 1993, represents the total effective resistances between all pairs of vertices in a graph G, where each edge is regarded a…
ACPO: Counteracting Likelihood Displacement in Vision-Language Alignment with Asymmetric Constraints
Kaili Huang, Hongming Zhang, Rui Shen +4
While Direct Preference Optimization (DPO) has become the de facto approach for aligning Large Vision-Language Models (LVLMs), it suffers from Likelihood Displacement, where the pr…
Enhancing the Outcome Reward-based RL Training of MLLMs with Self-Consistency Sampling
Jiahao Wang, Weiye Xu, Aijun Yang +5
Outcome-reward reinforcement learning (RL) is a common and increasingly significant way to refine the step-by-step reasoning of multimodal large language models (MLLMs). In the mul…
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…
ELV-Halluc: Benchmarking Semantic Aggregation Hallucinations in Long Video Understanding
Hao Lu, Jiahao Wang, Yaolun Zhang +5
Video multimodal large language models (Video-MLLMs) have achieved remarkable progress in video understanding. However, they remain vulnerable to hallucination-producing content in…
SEAL: Speech Embedding Alignment Learning for Speech Large Language Model with Retrieval-Augmented Generation
Chunyu Sun, Bingyu Liu, Zhichao Cui +5
Embedding-based retrieval models have made significant strides in retrieval-augmented generation (RAG) techniques for text and multimodal large language models (LLMs) applications.…