papers

Publications (31)

cs.CL2024

LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

Chi Han, Qifan Wang, Hao Peng +4

Today's large language models (LLMs) typically train on short text segments (e.g., <4K tokens) due to the quadratic complexity of their Transformer architectures. As a result, thei…

cs.SI2023

InfoPattern: Unveiling Information Propagation Patterns in Social Media

Chi Han, Jialiang Xu, Manling Li +3

Social media play a significant role in shaping public opinion and influencing ideological communities through information propagation. Our demo InfoPattern centers on the interpla…

cs.CL2025

Eliminating Position Bias of Language Models: A Mechanistic Approach

Ziqi Wang, Hanlin Zhang, Xiner Li +6

Position bias has proven to be a prevalent issue of modern language models (LMs), where the models prioritize content based on its position within the given context. This bias ofte…

cs.LG2024

LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning

Rui Pan, Xiang Liu, Shizhe Diao +4

The machine learning community has witnessed impressive advancements since large language models (LLMs) first appeared. Yet, their massive memory consumption has become a significa…

cs.CL2026

Neural Synchrony Between Socially Interacting Language Models

Zhining Zhang, Wentao Zhu, Chi Han +2

Neuroscience has uncovered a fundamental mechanism of our social nature: human brain activity becomes synchronized with others in many social contexts involving interaction. Tradit…

cs.CL2024

CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models

Cheng Qian, Chi Han, Yi R. Fung +3

Large Language Models (LLMs) have made significant progress in utilizing tools, but their ability is limited by API availability and the instability of implicit reasoning, particul…

cs.CV2020

Visual Concept-Metaconcept Learning

Chi Han, Jiayuan Mao, Chuang Gan +2

Humans reason with concepts and metaconcepts: we recognize red and green from visual input; we also understand that they describe the same property of objects (i.e., the color). In…

cs.LG2026

Protein Language Models Diverge from Natural Language: Comparative Analysis and Improved Inference

Anna Hart, Chi Han, Jeonghwan Kim +2

Modern Protein Language Models (PLMs) apply transformer-based model architectures from natural language processing to biological sequences, predicting a variety of protein function…

cs.SE2025

SyncMind: Measuring Agent Out-of-Sync Recovery in Collaborative Software Engineering

Xuehang Guo, Xingyao Wang, Yangyi Chen +4

Software engineering (SE) is increasingly collaborative, with developers working together on shared complex codebases. Effective collaboration in shared environments requires parti…

cs.CL2025

LDC: Learning to Generate Research Idea with Dynamic Control

Ruochen Li, Liqiang Jing, Chi Han +2

Recent advancements in large language models (LLMs) have demonstrated their potential in automating the scientific research ideation. Existing approaches primarily focus on prompti…

cs.CL2025

The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination

Yuji Zhang, Sha Li, Cheng Qian +8

Hallucination is a persistent challenge in large language models (LLMs), where even with rigorous quality control, models often generate distorted facts. This paradox, in which err…

cs.CL2023

Understanding the Effect of Data Augmentation on Knowledge Distillation

Ziqi Wang, Chi Han, Wenxuan Bao +1

Knowledge distillation (KD) requires sufficient data to transfer knowledge from large-scale teacher models to small-scale student models. Therefore, data augmentation has been wide…

cs.CL2023

Defining a New NLP Playground

Sha Li, Chi Han, Pengfei Yu +8

The recent explosion of performance of large language models (LLMs) has changed the field of Natural Language Processing (NLP) more abruptly and seismically than any other shift in…

cs.AI2023

Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning

Chi Han, Qizheng He, Charles Yu +3

Probabilistic logical rule learning has shown great strength in logical rule mining and knowledge graph completion. It learns logical rules to predict missing edges by reasoning on…

cs.CL2025

Can Language Models Follow Multiple Turns of Entangled Instructions?

Chi Han, Xin Liu, Haodong Wang +12

Despite significant achievements in improving the instruction-following capabilities of large language models (LLMs), the ability to process multiple potentially entangled or confl…

cs.CL2023

Zero-Shot Classification by Logical Reasoning on Natural Language Explanations

Chi Han, Hengzhi Pei, Xinya Du +1

Humans can classify data of an unseen category by reasoning on its language explanations. This ability is owing to the compositional nature of language: we can combine previously s…

cs.CL2021

Learning Shared Semantic Space for Speech-to-Text Translation

Chi Han, Mingxuan Wang, Heng Ji +1

Having numerous potential applications and great impact, end-to-end speech translation (ST) has long been treated as an independent task, failing to fully draw strength from the ra…

cs.CL2025

Understanding Emergent In-Context Learning from a Kernel Regression Perspective

Chi Han, Ziqi Wang, Han Zhao +1

Large language models (LLMs) have initiated a paradigm shift in transfer learning. In contrast to the classic pretraining-then-finetuning procedure, in order to use LLMs for downst…

cs.MA2021

Birds of a Feather Flock Together: A Close Look at Cooperation Emergence via Multi-Agent RL

Heng Dong, Tonghan Wang, Jiayuan Liu +2

How cooperation emerges is a long-standing and interdisciplinary problem. Game-theoretical studies on social dilemmas reveal that altruistic incentives are critical to the emergenc…

cs.LG2025

Transformers as Multi-task Learners: Decoupling Features in Hidden Markov Models

Yifan Hao, Chenlu Ye, Chi Han +1

Transformer based models have shown remarkable capabilities in sequence learning across a wide range of tasks, often performing well on specific task by leveraging input-output exa…

cs.CL2025

MentalArena: Self-play Training of Language Models for Diagnosis and Treatment of Mental Health Disorders

Cheng Li, May Fung, Qingyun Wang +4

Mental health disorders are one of the most serious diseases in the world. Most people with such a disease lack access to adequate care, which highlights the importance of training…

astro-ph.GA2024

Subhalos in Galaxy Clusters: Coherent Accretion and Internal Orbits

Chi Han, Kuan Wang, Camille Avestruz +1

Subhalo dynamics in galaxy cluster host halos govern the observed distribution and properties of cluster member galaxies. We use the IllustrisTNG simulation to investigate the accr…

astro-ph.IM2024

Prospects for using drones to test formation-flying CubeSat concepts, and other astronomical applications

John D. Monnier, Prachet Jain, Mayra Gutierrez +11

Drones provide a versatile platform for remote sensing and atmospheric studies. However, strict payload mass limits and intense vibrations have proven obstacles to adoption for ast…

cs.CL2024

Word Embeddings Are Steers for Language Models

Chi Han, Jialiang Xu, Manling Li +5

Language models (LMs) automatically learn word embeddings during pre-training on language corpora. Although word embeddings are usually interpreted as feature vectors for individua…

cs.AI2026

mCLM: A Modular Chemical Language Model that Generates Functional and Makeable Molecules

Carl Edwards, Chi Han, Gawon Lee +11

Despite their ability to understand chemical knowledge, large language models (LLMs) remain limited in their capacity to propose novel molecules with desired functions (e.g., drug-…

cs.CL2023

RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought

Tianci Xue, Ziqi Wang, Zhenhailong Wang +3

Large language Models (LLMs) have achieved promising performance on arithmetic reasoning tasks by incorporating step-by-step chain-of-thought (CoT) prompting. However, LLMs face ch…

cs.CL2024

Tool Learning with Foundation Models

Yujia Qin, Shengding Hu, Yankai Lin +38

Humans possess an extraordinary ability to create and utilize tools, allowing them to overcome physical limitations and explore new frontiers. With the advent of foundation models,…

cs.CL2024

Large Language Models on Graphs: A Comprehensive Survey

Bowen Jin, Gang Liu, Chi Han +3

Large language models (LLMs), such as GPT4 and LLaMA, are creating significant advancements in natural language processing, due to their strong text encoding/decoding ability and n…

cs.CL2025

Computation Mechanism Behind LLM Position Generalization

Chi Han, Heng Ji

Most written natural languages are composed of sequences of words and sentences. Similar to humans, large language models (LLMs) exhibit flexibility in handling textual positions -…

cs.AI2024

Schema-Guided Culture-Aware Complex Event Simulation with Multi-Agent Role-Play

Sha Li, Revanth Gangi Reddy, Khanh Duy Nguyen +7

Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society. Relying on historical events to project the f…

cs.CL2025

Towards LifeSpan Cognitive Systems

Yu Wang, Chi Han, Tongtong Wu +9

Building a human-like system that continuously interacts with complex environments -- whether simulated digital worlds or human society -- presents several key challenges. Central…