1 citations · 4 across the 15 of their papers we have counts for
15 papers
RuCL: Stratified Rubric-Based Curriculum Learning for Multimodal Large Language Model Reasoning
Yukun Chen, Jiaming Li, Longze Chen +10
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a prevailing paradigm for enhancing reasoning in Multimodal Large Language Models (MLLMs). However, relying sol…
Learning Ordinal Probabilistic Reward from Preferences
Longze Chen, Lu Wang, Qi Deng +7
Reward models are crucial for aligning large language models (LLMs) with human values and intentions. Existing approaches follow either Generative (GRMs) or Discriminative (DRMs) p…
AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
Jinghang Shi, Xiaoyu Tang, Yang Huang +4
Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…
Implicit Actor Critic Coupling via a Supervised Learning Framework for RLVR
Jiaming Li, Longze Chen, Ze Gong +5
Recent advances in Reinforcement Learning with Verifiable Rewards (RLVR) have empowered large language models (LLMs) to tackle challenging reasoning tasks such as mathematics and p…
STORYTELLER: An Enhanced Plot-Planning Framework for Coherent and Cohesive Story Generation
Jiaming Li, Yukun Chen, Ziqiang Liu +10
Stories are central to human culture, serving to share ideas, preserve traditions, and foster connections. Automatic story generation, a key advancement in artificial intelligence…
Breaking the Block: Preserving Data Continuity to Train Superior SAEs for Instruct Models
Jiaming Li, Haoran Ye, Yukun Chen +5
Sparse Autoencoders (SAEs) are a cornerstone of mechanistic interpretability. Existing training methods inherit the Block Training paradigm from LLM pre-training, which introduces…
IPBench: Benchmarking the Knowledge of Large Language Models in Intellectual Property
Qiyao Wang, Guhong Chen, Hongbo Wang +20
Intellectual Property (IP) is a highly specialized domain that integrates technical and legal knowledge, making it inherently complex and knowledge-intensive. Recent advancements i…
Kimi-VL Technical Report
Kimi Team, Angang Du, Bohong Yin +92
We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…
OpenOmni: Advancing Open-Source Omnimodal Large Language Models with Progressive Multimodal Alignment and Real-Time Self-Aware Emotional Speech Synthesis
Run Luo, Ting-En Lin, Haonan Zhang +10
Recent advancements in omnimodal learning have significantly improved understanding and generation across images, text, and speech, yet these developments remain predominantly conf…
Benchmarking Large Language Models for Image Classification of Marine Mammals
Yijiashun Qi, Shuzhang Cai, Zunduo Zhao +3
As Artificial Intelligence (AI) has developed rapidly over the past few decades, the new generation of AI, Large Language Models (LLMs) trained on massive datasets, has achieved gr…
PersonaMath: Boosting Mathematical Reasoning via Persona-Driven Data Augmentation
Jing Luo, Longze Chen, Run Luo +12
While closed-source Large Language Models (LLMs) demonstrate strong mathematical problem-solving abilities, open-source models still face challenges with such tasks. To bridge this…
Ruler: A Model-Agnostic Method to Control Generated Length for Large Language Models
Jiaming Li, Lei Zhang, Yunshui Li +5
The instruction-following ability of large language models enables humans to interact with AI agents in a natural way. However, when required to generate responses of a specific le…
Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs
Lei Zhang, Yunshui Li, Jiaming Li +7
Some recently developed code large language models (Code LLMs) have been pre-trained on repository-level code data (Repo-Code LLMs), enabling these models to recognize repository s…
II-Bench: An Image Implication Understanding Benchmark for Multimodal Large Language Models
Ziqiang Liu, Feiteng Fang, Xi Feng +23
The rapid advancements in the development of multimodal large language models (MLLMs) have consistently led to new breakthroughs on various benchmarks. In response, numerous challe…
Instruction-Guided Visual Masking
Jinliang Zheng, Jianxiong Li, Sijie Cheng +6
Instruction following is crucial in contemporary LLM. However, when extended to multimodal setting, it often suffers from misalignment between specific textual instruction and targ…