5 citations · 7 across the 11 of their papers we have counts for
14 papers
World Embedding Benchmark
Yiqi Liu, Ruifeng Yuan, Yang Wang +7
Physical fidelity has received increasing attention in world models and video generation, yet how video representations encode physical information remains less understood. We intr…
AutoDataBench: A Data-centric Testbed for Accelerating Auto Research
Ruifeng Yuan, Yizhi Li, Yaxin Du +9
Existing auto-research benchmarks often entangle multiple sources of improvement, including training frameworks, hyperparameters, compute budgets, and data, making it difficult to…
On the Design Fundamentals of Pixel Text Representation Learning
Chaohao Yuan, Ruifeng Yuan, Zhuoxu Huang +4
Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders struggle with fixed resolution pretr…
Beyond Entropy: Correctness-Aware Advantage Shaping via Contrastive Policy Optimization
Weiwen Xu, Jia Liu, Hou Pong Chan +4
Reinforcement learning with verifiable rewards (RLVR) commonly uses entropy for advantage shaping. However, entropy cannot distinguish useful uncertainty from detrimental confusion…
Understanding the Behaviors of Environment-aware Information Retrieval
Ruifeng Yuan, Chaohao Yuan, David Dai +4
Recent retrieval-augmented generation (RAG) approaches have demonstrated strong capability in handling complex queries, yet current research overlooks a critical challenge: differe…
SeaLLMs-Audio: Large Audio-Language Models for Southeast Asia
Chaoqun Liu, Mahani Aljunied, Guizhen Chen +4
We introduce SeaLLMs-Audio, the first large audio-language model (LALM) tailored for multiple Southeast Asian (SEA) languages-Indonesian (id), Thai (th), and Vietnamese (vi)-alongs…
VL-Cogito: Progressive Curriculum Reinforcement Learning for Advanced Multimodal Reasoning
Ruifeng Yuan, Chenghao Xiao, Sicong Leng +9
Reinforcement learning has proven its effectiveness in enhancing the reasoning capabilities of large language models. Recent research efforts have progressively extended this parad…
Lingshu: A Generalist Foundation Model for Unified Multimodal Medical Understanding and Reasoning
LASA Team, Weiwen Xu, Hou Pong Chan +16
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in understanding common visual elements, largely due to their large-scale datasets and advanced t…
Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
Chenghao Xiao, Hou Pong Chan, Hao Zhang +4
While understanding the knowledge boundaries of LLMs is crucial to prevent hallucination, research on the knowledge boundaries of LLMs has predominantly focused on English. In this…
Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers
Yiran Zhao, Chaoqun Liu, Yue Deng +8
Large language models (LLMs) have revolutionized natural language processing (NLP), yet open-source multilingual LLMs remain scarce, with existing models often limited in language…
FINEREASON: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving
Guizhen Chen, Weiwen Xu, Hao Zhang +6
Many challenging reasoning tasks require not just rapid, intuitive responses, but a more deliberate, multi-step approach. Recent progress in large language models (LLMs) highlights…
M-Longdoc: A Benchmark For Multimodal Super-Long Document Understanding And A Retrieval-Aware Tuning Framework
Yew Ken Chia, Liying Cheng, Hou Pong Chan +5
The ability to understand and answer questions over documents can be useful in many business and practical applications. However, documents often contain lengthy and diverse multim…
VisAidMath: Benchmarking Visual-Aided Mathematical Reasoning
Jingkun Ma, Runzhe Zhan, Yang Li +4
A hallmark of advanced artificial intelligence is the capacity to progress from passive visual perception to the strategic modification of visual information to facilitate complex…
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages
Wenxuan Zhang, Hou Pong Chan, Yiran Zhao +9
Large Language Models (LLMs) have shown remarkable abilities across various tasks, yet their development has predominantly centered on high-resource languages like English and Chin…