Publications (25)
Monotonicity Marking from Universal Dependency Trees
Zeming Chen, Qiyue Gao
Dependency parsing is a tool widely used in the field of Natural language processing and computational linguistics. However, there is hardly any work that connects dependency parsi…
Using a virtual reality interview simulator to explore factors influencing people's behavior
Xinyi Luo, Yuyang Wang, Lik-Hang Lee +7
Virtual reality interview simulator (VRIS) provides an effective and manageable approach for candidates prone to being very nervous during interviews, yet, the major anxiety-induci…
RECKONING: Reasoning through Dynamic Knowledge Encoding
Zeming Chen, Gail Weiss, Eric Mitchell +2
Recent studies on transformer-based language models show that they can answer questions by reasoning over knowledge provided as part of the context (i.e., in-context reasoning). Ho…
Discovering Knowledge-Critical Subnetworks in Pretrained Language Models
Deniz Bayazit, Negar Foroutan, Zeming Chen +2
Pretrained language models (LMs) encode implicit representations of knowledge in their parameters. However, localizing these representations and disentangling them from each other…
Mixed Pseudo Labels for Semi-Supervised Object Detection
Zeming Chen, Wenwei Zhang, Xinjiang Wang +2
While the pseudo-label method has demonstrated considerable success in semi-supervised object detection tasks, this paper uncovers notable limitations within this approach. Specifi…
Probing Linguistic Information For Logical Inference In Pre-trained Language Models
Zeming Chen, Qiyue Gao
Progress in pre-trained language models has led to a surge of impressive results on downstream tasks for natural language understanding. Recent work on probing pre-trained language…
Could ChatGPT get an Engineering Degree? Evaluating Higher Education Vulnerability to AI Assistants
Beatriz Borges, Negar Foroutan, Deniz Bayazit +87
AI assistants are being increasingly used by students enrolled in higher education institutions. While these tools provide opportunities for improved teaching and education, they a…
V3Det Challenge 2024 on Vast Vocabulary and Open Vocabulary Object Detection: Methods and Results
Jiaqi Wang, Yuhang Zang, Pan Zhang +31
Detecting objects in real-world scenes is a complex task due to various challenges, including the vast range of object categories, and potential encounters with previously unknown…
PhysEditBench: A Protocol-Conditioned Benchmark for Dense Physical-Map Prediction with Image Editors
Jiaxin Yang, Yu Hou, Muxin Liu +5
Can general-purpose image editors predict physical maps from a single RGB image? General-purpose image editors differ from standard task-specific dense-prediction models: they do n…
DynaVieW: Schema-Guided World Modeling for Understanding Hierarchical Visual Dynamics
Silin Gao, Hao Zhao, Zeming Chen +8
Multimodal LLMs struggle to systematically model the temporal evolution of visual scenes in videos or multi-image sequences. Such inputs require models to predict or simulate multi…
Attentive Tree-structured Network for Monotonicity Reasoning
Zeming Chen
Many state-of-art neural models designed for monotonicity reasoning perform poorly on downward inference. To address this shortcoming, we developed an attentive tree-structured neu…
Do Vision-Language Models Have Internal World Models? Towards an Atomic Evaluation
Qiyue Gao, Xinyu Pi, Kevin Liu +21
Internal world models (WMs) enable agents to understand the world's state and predict transitions, serving as the basis for advanced deliberative reasoning. Recent large Vision-Lan…
Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language Understanding
Zeming Chen, Qiyue Gao
In the age of large transformer language models, linguistic evaluation play an important role in diagnosing models' abilities and limitations on natural language understanding. How…
Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs
Tianqing Fang, Zeming Chen, Yangqiu Song +1
Event commonsense reasoning requires the ability to reason about the relationship between events, as well as infer implicit context underlying that relationship. However, data scar…
Tracking the Limits of Knowledge Propagation: How LLMs Fail at Multi-Step Reasoning with Conflicting Knowledge
Yiyang Feng, Zeming Chen, Haotian Wu +2
A common solution for mitigating outdated or incorrect information in Large Language Models (LLMs) is to provide updated facts in-context or through knowledge editing. However, the…
NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning
Zeming Chen, Qiyue Gao, Lawrence S. Moss
Deep learning (DL) based language models achieve high performance on various benchmarks for Natural Language Inference (NLI). And at this time, symbolic approaches to NLI are recei…
MICSim: A Modular Simulator for Mixed-signal Compute-in-Memory based AI Accelerator
Cong Wang, Zeming Chen, Shanshi Huang
This work introduces MICSim, an open-source, pre-circuit simulator designed for early-stage evaluation of chip-level software performance and hardware overhead of mixed-signal comp…
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models
Zeming Chen, Alejandro Hernández Cano, Angelika Romanou +17
Large language models (LLMs) can potentially democratize access to medical knowledge. While many efforts have been made to harness and improve LLMs' medical knowledge and reasoning…
Mitigating Label Biases for In-context Learning
Yu Fei, Yifan Hou, Zeming Chen +1
Various design settings for in-context learning (ICL), such as the choice and order of the in-context examples, can bias a model toward a particular prediction without being reflec…
PERK: Long-Context Reasoning as Parameter-Efficient Test-Time Learning
Zeming Chen, Angelika Romanou, Gail Weiss +1
Long-context reasoning requires accurately identifying relevant information in extensive, noisy input contexts. Previous research shows that using test-time learning to encode cont…
Mixture of Cognitive Reasoners: Modular Reasoning with Brain-Like Specialization
Badr AlKhamissi, C. Nicolò De Sabbata, Greta Tuckute +3
Human cognitive behavior arises from the interaction of specialized brain networks dedicated to distinct functions, such as language, logic, and social reasoning. Inspired by this…
DISCO: Distilling Counterfactuals with Large Language Models
Zeming Chen, Qiyue Gao, Antoine Bosselut +2
Models trained with counterfactually augmented data learn representations of the causal structure of tasks, enabling robust generalization. However, high-quality counterfactual dat…
BEV-VAE: Multi-view Image Generation with Spatial Consistency for Autonomous Driving
Zeming Chen, Hang Zhao
Multi-view image generation in autonomous driving demands consistent 3D scene understanding across camera views. Most existing methods treat this problem as a 2D image set generati…
GeoExplorer: Active Geo-localization with Curiosity-Driven Exploration
Li Mi, Manon Bechaz, Zeming Chen +2
Active Geo-localization (AGL) is the task of localizing a goal, represented in various modalities (e.g., aerial images, ground-level images, or text), within a predefined search ar…
INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge
Angelika Romanou, Negar Foroutan, Anna Sotnikova +56
The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…