9 citations · 20 across the 18 of their papers we have counts for
19 papers
FinanceComplexQA: Benchmarking Agentic Reasoning on Industrial-grade Financial Documents
Xianfu Cheng, Shiwei Zhang, Jiyu Zhao +10
Agentic Reasoning has become a transformative force in financial analysis due to its ability to integrate large-scale information and generate reliable and accurate content. Howeve…
Persona Non Grata: LLM Persona-Driven Generations in MCQA are Unstable in Distinct Dimensions
César Guerra-Solano, Xiang Lorraine Li
Persona-driven generations (PDGs) have seen prolific use in research and industry applications, where a large language model (LLM) takes on a 'persona' while completing some task.…
SAGE: Scalable AI Governance & Evaluation
Benjamin Le, Xueying Lu, Nick Stern +17
Evaluating relevance in large-scale search systems is fundamentally constrained by the governance gap between nuanced, resource-constrained human oversight and the high-throughput…
GhostCite: A Large-Scale Analysis of Citation Validity in the Age of Large Language Models
Zuyao Xu, Yuqi Qiu, Lu Sun +14
Citations provide the basis for trusting scientific claims; when they are invalid or fabricated, this trust collapses. With the advent of Large Language Models (LLMs), this risk ha…
An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models
Xinxin Lin, Guangxin Dai, Yi Zhong +25
Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requires substantial data and expert a…
RATE: Reviewer Profiling and Annotation-free Training for Expertise Ranking in Peer Review Systems
Weicong Liu, Zixuan Yang, Yibo Zhao +1
Reviewer assignment is increasingly critical yet challenging in the LLM era, where rapid topic shifts render many pre-2023 benchmarks outdated and where proxy signals poorly reflec…
Embodied Task Planning via Graph-Informed Action Generation with Large Language Models
Xiang Li, Ning Yan, Masood Mortazavi
While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundamental challenges in long-horizon…
ChartAgent: A Chart Understanding Framework with Tool Integrated Reasoning
Boran Wang, Xinming Wang, Yi Chen +4
With their high information density and intuitive readability, charts have become the de facto medium for data analysis and communication across disciplines. Recent multimodal larg…
Think Globally, Group Locally: Evaluating LLMs Using Multi-Lingual Word Grouping Games
César Guerra-Solano, Zhuochun Li, Xiang Lorraine Li
Large language models (LLMs) can exhibit biases in reasoning capabilities due to linguistic modality, performing better on tasks in one language versus another, even with similar c…
RoRecomp: Enhancing Reasoning Efficiency via Rollout Response Recomposition in Reinforcement Learning
Gang Li, Yulei Qin, Xiaoyu Tan +6
Reinforcement learning with verifiable rewards (RLVR) has proven effective in eliciting complex reasoning in large language models (LLMs). However, standard RLVR training often lea…
MMBERT: Scaled Mixture-of-Experts Multimodal BERT for Robust Chinese Hate Speech Detection under Cloaking Perturbations
Qiyao Xue, Yuchen Dou, Ryan Shi +2
Hate speech detection on Chinese social networks presents distinct challenges, particularly due to the widespread use of cloaking techniques designed to evade conventional text-bas…
VideoMultiAgents: A Multi-Agent Framework for Video Question Answering
Noriyuki Kugo, Xiang Li, Zixin Li +9
Video Question Answering (VQA) inherently relies on multimodal reasoning, integrating visual, temporal, and linguistic cues to achieve a deeper understanding of video content. Howe…
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
Juncheng Wu, Wenlong Deng, Xingxuan Li +12
Medical tasks such as diagnosis and treatment planning require precise and complex reasoning, particularly in life-critical domains. Unlike mathematical reasoning, medical reasonin…
Towards deployment-centric multimodal AI beyond vision and language
Xianyuan Liu, Jiayang Zhang, Shuo Zhou +45
Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction, and decision-making across disciplines such as h…
Similarity-Based Domain Adaptation with LLMs
Jie He, Wendi Zhou, Xiang Lorraine Li +1
Unsupervised domain adaptation leverages abundant labeled data from various source domains to generalize onto unlabeled target data. Prior research has primarily focused on learnin…
SimpleVQA: Multimodal Factuality Evaluation for Multimodal Large Language Models
Xianfu Cheng, Wei Zhang, Shiwei Zhang +16
The increasing application of multi-modal large language models (MLLMs) across various sectors have spotlighted the essence of their output reliability and accuracy, particularly t…
"See the World, Discover Knowledge": A Chinese Factuality Evaluation for Large Vision Language Models
Jihao Gu, Yingyao Wang, Pi Bu +17
The evaluation of factual accuracy in large vision language models (LVLMs) has lagged behind their rapid development, making it challenging to fully reflect these models' knowledge…
Statically Contextualizing Large Language Models with Typed Holes
Andrew Blinn, Xiang Li, June Hyung Kim +1
Large language models (LLMs) have reshaped the landscape of program synthesis. However, contemporary LLM-based code completion systems often hallucinate broken code because they la…
Persuasiveness of Generated Free-Text Rationales in Subjective Decisions: A Case Study on Pairwise Argument Ranking
Mohamed Elaraby, Diane Litman, Xiang Lorraine Li +1
Generating free-text rationales is among the emergent capabilities of Large Language Models (LLMs). These rationales have been found to enhance LLM performance across various NLP t…