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ORCID2nd Tiny Papers @ ICLR 2024: Vienna, Austria
- The Second Tiny Papers Track at ICLR 2024, Tiny Papers @ ICLR 2024, Vienna, Austria, May 11, 2024. OpenReview.net 2024
Invite to present (notable)
- Veronika Ganeeva, Kuzma Khrabrov, Artur Kadurin, Andrey V. Savchenko, Elena Tutubalina:
Chemical Language Models Have Problems with Chemistry: A Case Study on Molecule Captioning Task. - Gargi Singh, Milind Tambe, Aparna Taneja:
Towards Fairness constrained Restless Multi-Armed Bandits: a Case Study of Maternal and child Care Domain. - Lele Liu, Christof Weiss:
Utilizing Cross-Version Consistency for Domain Adaptation: A Case Study on Music Audio. - Lilian Ngweta, Mayank Agarwal, Subha Maity, Alex Gittens, Yuekai Sun, Mikhail Yurochkin:
Aligners: Decoupling LLMs and Alignment. - Ziniu Li, Tian Xu, Yang Yu:
When is RL better than DPO in RLHF? A Representation and Optimization Perspective. - Tarun Suresh, Shubham Ugare, Gagandeep Singh
, Sasa Misailovic:
Is Watermarking LLM-Generated Code Robust? - Debanjan Dutta, Anish Chakrabarty, Swagatam Das:
Lost in Translation: GANs' Inability to Generate Simple Probability Distributions. - Faroq Al-Tam, Muhammad Al-Qurishi, Thariq Khalid Kadavil, Riad Souissi:
CMFPN: Context Modeling Meets Feature Pyramid Network. - Yijingxiu Lu, Yinhua Piao, Sun Kim:
Enhancing Drug-Drug Interaction Prediction with Context-Aware Architecture. - Chen Zhang, Mingxu Tao, Quzhe Huang, Zhibin Chen, Yansong Feng:
Can LLMs Learn a New Language on the Fly? A Case Study on Zhuang. - Shreya Ghosh, Yi-Huan Chen, Ching-Hsiang Huang, Abu Shafin Mohammad Mahdee Jameel, Aly El Gamal, Samuel Labi:
Weighted Branch Aggregation Based Deep Learning Model for Track Detection in Autonomous Racing. - Kunal Singh, Mukund Khanna, Ankan Biswas, Pradeep Moturi, Shivam:
Visual prompting Methods for GPT-4V based Zero-Shot Graphic Layout Design Generation. - Jordan Dotzel, Bahaa Kotb, James Dotzel, Mohamed S. Abdelfattah, Zhiru Zhang:
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel. - Chaehyeon Kim, Weiqiu You, Shreya Havaldar, Eric Wong:
Evaluating Groups of Features via Consistency, Contiguity, and Stability. - Muzi Tao, Saining Xie:
What Does a Visual Formal Analysis of the World's 500 Most Famous Paintings Tell Us About Multimodal LLMs? - Matthew Hull, Zijie J. Wang, Duen Horng Chau:
Revamp: Automated Simulations of Adversarial Attacks on Arbitrary Objects in Realistic Scenes. - Santtu Keskinen:
Hard ASH: Sparsity and the right optimizer make a continual learner. - Imane Hamzaoui, Hadjer Benmeziane, Zayneb Cherif, Kaoutar El Maghraoui:
Analog In-Memory Computing with Uncertainty Quantification for Efficient Edge-based Medical Imaging Segmentation. - Anas Mohammad Ishfaqul Muktadir Osmani, Taimur Rahman, Salekul Islam:
VoltaVision: A Transfer Learning model for electronic component classification. - Fateme Vesaghati, Masoumeh Zareapoor:
Training Mixture-of-Experts: A Focus on Expert-Token Matching. - Yusuf Brima, Ulf Krumnack, Simone Pika, Gunther Heidemann:
Learning Disentangled Audio Representations through Controlled Synthesis. - David Herel, Tomás Mikolov:
Collapse of Self-trained Language Models. - Libo Huang, Zhulin An, Yan Zeng, Xiang Zhi, Yongjun Xu:
KFC: Knowledge Reconstruction and Feedback Consolidation Enable Efficient and Effective Continual Generative Learning. - Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko:
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better. - Zixuan Liu, Liu Liu, Xueqian Wang, Peilin Zhao:
DFWLayer: Differentiable Frank-Wolfe Optimization Layer. - Jiahui Li, Pourya Shamsolmoali:
3D Shape Completion via Sparse Irregular Representation. - Aishik Nagar, Shantanu Jaiswal, Cheston Tan:
Dissecting Zero-Shot Visual Reasoning Capabilities in Vision and Language Models. - Md. Faiyaz Abdullah Sayeedi, Fahim Hafiz, Md Ashiqur Rahman:
MosquitoFusion: A Multiclass Dataset for Real-Time Detection of Mosquitoes, Swarms, and Breeding Sites Using Deep Learning. - Hamidreza Eivazi, Stefan H. A. Wittek, Andreas Rausch:
Nonlinear model reduction for operator learning. - Zhiming Li, Junzhe Jiang, Yushi Cao, Aixin Cui, Bozhi Wu, Bo Li, Yang Liu:
Logic-guided Deep Reinforcement Learning for Stock Trading. - Weili Kong, Baisen Liu, Xiaojun Bi, Jiaming Pei:
A Shared Encoder for Multi-Source Hyperspectral Images. - Xin Li, Siqi Li, Qiming Wu, Kunyu Yu:
Transfer Learning for Global Feature Importance Measurements. - Guobin Shen, Dongcheng Zhao, Sicheng Shen, Yi Zeng:
Enhancing Spiking Transformers with Binary Attention Mechanisms. - Jing Xu, Beiwen Tian, Hao Zhao:
Key Patch Proposer: Key Patches Contain Rich Information. - Jinge Wu, Yunsoo Kim, Honghan Wu:
Hallucination Benchmark in Medical Visual Question Answering. - Víctor Gallego:
Distilled Self-Critique of LLMs with Synthetic Data: a Bayesian Perspective. - Aryan Garg:
Parameter and Data Efficient Spectral Style-DCGAN. - Aryan Garg, Renu Rameshan:
G-PECNet: Towards a Generalizable Pedestrian Trajectory Prediction System. - Juhwan Choi, YoungBin Kim:
Colorful Cutout: Enhancing Image Data Augmentation with Curriculum Learning.
Invite to present
- Uladzislau Yorsh, Martin Holena, Ondrej Bojar, David Herel:
On Difficulties of Attention Factorization through Shared Memory. - Simon Frieder, Luca Pinchetti, Thomas Lukasiewicz:
Bad Predictive Coding Activation Functions. - Jasdeep Sidhu, Shubhra Mishra, Aryan Gulati, Devanshu Ladsaria, Brando Miranda:
An Evaluation Benchmark for Autoformalization in Lean4. - Maral Jabbarishiviari, Arshia Soltani Moakhar:
Software 1.0 Strengths for Interpretability and Data Efficiency. - Dyutit Mohanty, Aditya Kasliwal, Bharath Udupa, Pratinav Seth:
Sailing Through Spectra: Unveiling the Potential of Multi-Spectral Information in Marine Debris Segmentation. - Pirzada Suhail:
Network Inversion of Binarised Neural Nets. - Samyak Jain, Parth Chhabra, Ramit Sawhney:
Uncovering Bias: Exploring Gender Dynamics in Distance-Aware Mixup Techniques. - Zihan Qiu, Zeyu Huang, Youcheng Huang, Jie Fu:
Empirical Study on Updating Key-Value Memories in Transformer Feed-forward Layers. - Azmine Toushik Wasi, Karlo Serbetar, Raima Islam, Taki Hasan Rafi, Dong-Kyu Chae:
When SMILES have Language: Drug Classification using Text Classification Methods on Drug SMILES Strings. - Arnav Goel, Medha Hira, Anubha Gupta:
Multilingual Prosody Transfer: Comparing Supervised & Transfer Learning. - Saptarshi Saha, Utpal Garain:
Region Mixup. - Moshiur Rahman, Muhtasim Ishmum Khan, Md. Shahriar Karim:
Design of a molecular exchange-based robust perceptron for biomolecular neural network. - Simon Frieder, Mirek Olsák, Julius Berner, Thomas Lukasiewicz:
The IMO Small Challenge: Not-Too-Hard Olympiad Math Datasets for LLMs. - Chinmay Rane, Kanishka Tyagi, Tushar Chugh, Nirmala Murali:
Dynamic Activations for Neural Net Training. - Kshitij Kapoor, Debayan Gupta:
Non Parametric Aleatoric Uncertainty Quantification with Neural Networks. - Vinayak Gupta, Manoj S., Mukund Varma T., Kaushik Mitra:
U2NeRF: Unsupervised Underwater Image Restoration and Neural Radiance Fields. - Akash Guna R. T., Arnav Chavan, Deepak K. Gupta:
Beyond Uniform Scaling: Exploring Depth Heterogeneity in Neural Architectures. - Aditya Singh, Aditi Singla, Kanishk Kukreja:
A Bi-Objective $\epsilon $-Constrained Framework for Quality-Cost Optimization in Language Model Ensembles. - Evan Gerritz, Luciano Dyballa, Steven W. Zucker:
Zero-shot generalization across architectures for visual classification. - Mohammad Aflah Khan, Neemesh Yadav, Diksha Sethi, Raghav Sahni:
The Duality of Hope: A Critical Examination of Controversial Annotations in HopeEDI. - Zundong Wu, Jin Xu:
DynamicPoseNet: Advanced Human Motion Generation with Dual-Pathway CNNs and LoRA-Enhanced LLaMA. - Medha Hira, Arnav Goel, Anubha Gupta:
CrossVoice: Crosslingual Prosody Preserving Cascade-S2ST using Transfer Learning. - Samyak Jain, Rishi Singhal, Sriram Krishna, Yaman Kumar Singla, Rajiv Ratn Shah:
Beyond Words: A Topological Exploration of Coherence in Text Documents. - Lukasz Sztukiewicz, Jack Henry Good, Artur Dubrawski:
Exploring Loss Design Techniques For Decision Tree Robustness To Label Noise. - Evan Mitchell, Biswajit Basu, Pabitra Mitra:
Performance Analysis of a quantum-Classical Hybrid Reinforcement Learning Approach. - Jason Vega, Isha Chaudhary, Changming Xu, Gagandeep Singh:
Bypassing the Safety Training of Open-Source LLMs with Priming Attacks. - Aref Tabatabaei, Zahra Dehghanian, Negar Movaghatian, Maryam Amirmazlaghani:
No More BLAH-BLAH: Embracing Real Text in the Image synthesis World. - Borui Cai, Zihao Johnson Zheng, Longxiang Gao, Yong Xiang:
Borderline Sample Extraction from a Trained Classifier. - Cheng Chen, Ivor W. Tsang:
Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision. - Skye Gunasekaran, Jason Eshraghian, Ruomin Zhu, Zdenka Kuncic:
Knowledge Distillation Through Time For Future Event Prediction. - Yutong Hu, Quzhe Huang, Mingxu Tao, Chen Zhang, Yansong Feng:
Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding? - Hanqing Lu, Xianfeng Tang, Chen Luo, Limeng Cui, Zhenwei Dai, Rahul Goutam, Haiyang Zhang, Monica Xiao Cheng:
Session-Aware Product filter Ranking in E- Commerce Search. - Han Xu, Jingyang Ye, Yutong Li, Haipeng Chen:
Can Speculative Sampling Accelerate ReAct Without Compromising Reasoning Quality? - Arnav Chavan, Nahush Lele, Deepak K. Gupta:
Rethinking Compression: Reduced order modelling of Latent Features in Large Language Models. - Matthew Lau, Leyan Pan, Stefan Davidov, Athanasios P. Meliopoulos, Wenke Lee:
Geometric Implications of Classification on Reducing Open Space Risk. - Simranjit Singh, Aditya Golatkar, Avijit Verma:
Role of Over-Parameterization in Generalization of 3-layer ReLU Networks. - Srilekha Geda, Chunjiang Zhu:
Density-Preserving Heterogeneous Graph Sparsification for Representation Learning. - Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez:
Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping. - Rushikesh Zawar, Prabhdeep Singh Sethi, Roshan Roy:
Jensen-Shannon Divergence in Safe Multi- Agent RL. - Harman Singh Farwah, Gagandeep Singh, Cheng Tan:
Exploiting Time Channel Vulnerability of Learned Bloom Filters. - Mohamed Osman, Daniel Z. Kaplan:
Small Transformers, Big Results: Efficient Diffusion with Parameter Sharing. - Mohammad Taha Teimuri Jervakani, Zahra Dehghanian, Gholamali Aminian, Hamid R. Rabiee:
KLCE: Regularized Imbalance Node-classification Via KL-divergence and Cross-Entropy. - Indranil Ojha, Kushal Bose, Swagatam Das:
Affinity-based Homophily: Can we measure homophily of a graph without using node labels? - Siddhant Bikram Shah:
Can Decoupling Embedded Text from Images Improve Multimodal Learning? - Zhicheng Du, Zhaotian Xie, Huazhang Ying, Likun Zhang, Peiwu Qin:
Cognitive resilience: Unraveling the proficiency of image-captioning models to interpret masked visual content. - Gianluca Moro, Luca Ragazzi, Lorenzo Valgimigli, Fabian Vincenzi, Davide Freddi:
Revelio: Interpretable Long-Form Question Answering. - Jack Foster, Stefan Schoepf, Alexandra Brintrup:
Loss-Free Machine Unlearning. - Will Rowan, Patrik Huber, Nick E. Pears, Andrew Keeling:
How Many OptiFaces? A New Evaluation Metric For 3D Face Reconstruction. - Ramit Sawhney, Megh Thakkar:
Sequence Mixup for Zero-Shot Cross-Lingual Part-of-speech Tagging. - Ruochen Cui, Yongding Tao, Mingjun Ni:
A Novel Window-Interaction Module Based on W-MSA. - Hieu Le Xuan, Minh Hoang Le, Viet V. Truong, Huy Phan Quang, Hoang Vu Huy:
Mask2tasks: Leveraging Segmentation to Enhance Classification Performance in histopathological colorectal Images. - Tao Ma, Xuzhi Yang:
A Framework for Policy Evaluation Enhancement by Diffusion Models. - Chendong Xiang, Armando Teles Fortes, Khang Hui Chua, Hang Su, Jun Zhu:
FeedFace: Efficient Inference-based Face Personalization via Diffusion Models. - Peihua Mai, Hao Jiang, Ran Yan, Youjia Yang, Zhe Huang, Yan Pang:
Knowledge Graph Unlearning to Defend Language Model Against Jailbreak Attack. - Julian Rodemann, Hannah Blocher:
Partial Rankings of Optimizers. - Mansi Phute, Alec Helbling, Matthew Hull, Shengyun Peng, Sebastian Szyller, Cory Cornelius, Duen Horng Chau:
LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked. - Xiaomeng Wang, Dharmendra Sharma, Dinesh Kumar:
Cognitive Reframing via Large Language Models for Enhanced Linguistic Attributes. - Oriel Perets, Nadav Rappoport:
DSF-GAN: Downstream Feedback Generative Adversarial Network. - Anas Mohammed Alhumud, Muhammad Al-Qurishi, Yasser Omar Alomar, Ali Alzahrani, Riad Souissi:
Improving Automated Speech Recognition Using Retrieval-Based Voice Conversion. - Manan Suri, Puneet Mathur, Ramit Sawhney, Preslav Nakov, Dinesh Manocha:
Doc2Command: Furthering Language Guided Document Editing. - Azmine Toushik Wasi:
Neural Control System for Continuous Glucose Monitoring and Maintenance. - Menglin Li, Kwan Hui Lim:
Enhancing Language Models for Financial Relation Extraction with Named Entities and Part-of-Speech. - Ciyuan Peng, Mujie Liu, Chenxuan Meng, Shuo Yu, Feng Xia:
Adaptive Brain Network Augmentation Based on Group-aware Graph Learning. - Rubén Ruiz-Torrubiano:
Generating Counterfactual Explanations Using Cardinality Constraints. - Wenchuan Mu, Kwan Hui Lim:
Explicitly Stating Assumptions Reduces Hallucinations in Natural Language Inference. - Ishani Mondal, Abhilasha Sancheti:
On the robustness of Chatgpt under input perturbations for Named Entity Recognition Task. - Lingyi Yang, Zhen Shao:
Neural Controlled Differential Equations with Quantum Hidden Evolutions. - Lisa Schneckenreiter, Richard Freinschlag, Florian Sestak, Johannes Brandstetter, Günter Klambauer, Andreas Mayr:
GNN-VPA: A Variance-Preserving Aggregation Strategy for Graph Neural Networks. - Zheng Luan, Xiangqi Kong, Shuimu Zeng, Yuke Yao, Yaxuan Zhang, Xuerui Qiu:
Using spiking neural networks to assist fine art and philology study: to classify styles of Chinese calligraphy with minimal computing power. - Thomas Kreutz, Max Mühlhäuser, Alejandro Sánchez Guinea:
Common Sense Initialization of Mixture Density Networks for Motion Planning with Overestimated Number of Components. - Frederic Boesel, Robin Rombach:
Improving Image Editing Models with Generative Data Refinement. - Navdeep Kumar, Kaixin Wang, Uri Gadot, Kfir Yehuda Levy, Shie Mannor:
Learning the Uncertainty Set in Robust Markov Decision Process. - Xiao Cui, Qi Sun, Wengang Zhou, Houqiang Li:
Exploring GPT-4 Vision for Text-to-Image Synthesis Evaluation. - Adrián Bazaga, Pietro Lio, Gos Micklem:
Language Model Knowledge Distillation for Efficient Question Answering in Spanish. - Ritabrata Maiti:
AdAct: Learning to Optimize Activation Function Choice through Adaptive Activation Modules. - Yuejy, Xiaojun Bi, Zheng Chen:
A Novel Two-stage Model with Cross-Level Contrastive Learning for Text-VQA. - Xiao Cui, Wengang Zhou, Houqiang Li:
Heredity-aware Child Face Image Generation with Latent Space Disentanglement. - Blaine Hoak, Patrick D. McDaniel:
Explorations in Texture Learning. - Yasaman Razeghi, Hamish Ivison, Sameer Singh, Yanai Elazar:
Backtracking Mathematical Reasoning of Language Models to the Pretraining Data. - Zhiyu An, Xianzhong Ding, Wan Du:
Reward Bound for Behavioral Guarantee of Model-based Planning Agents. - Manuel Dileo, Matteo Zignani:
Can Graph Neural Networks learn node-level structural features? - Md. Kowsher, Md. Shohanur Islam Sobuj, Asif Mahmud, Nusrat Jahan Prottasha, Prakash Bhat:
L-Tuning: Synchronized Label Tuning for Prompt and Prefix in LLMS. - C. Coelho, M. Fernanda P. Costa, Luís L. Ferrás:
Tracing Footprints: Neural Networks Meet Non-integer Order Differential Equations For Modelling Systems with Memory. - Priyanshu Kumar Rai, Pratik Pal, Akshay Agarwal:
A Generalized Semiconductor Wafer Defect Classifier. - Daragh King:
Using the Polyak Step Size in training Convolutional Neural Networks. - Sai Aparna Aketi, Sakshi Choudhary, Kaushik Roy:
Averaging Rate Scheduler for Decentralized Learning on Heterogeneous Data. - Kirtilekha Bhesra, Shivam Ashok Shukla, Akshay Agarwal:
Audio vs. Text: Identify a Powerful Modality for Effective Hate Speech Detection. - Satoki Ishikawa, Rio Yokota:
When Does Second-Order Optimization Speed Up Training? - Ahmad Ayaz Amin:
Discrete Natural Evolution Strategies. - Urchade Zaratiana:
Lost or Liberated? A Dive into Bidirectional Transformer LMs Without Positional Encoding. - Navdeep Kumar, Priyank Agrawal, Kfir Yehuda Levy, Shie Mannor:
Policy Gradient with Tree Search (PGTS) in Reinforcement Learning Evades Local Maxima. - Chengao Shen, Siyuan Mu, Ge Diao:
Emoji Kitchen with Controlled Fusion. - Yuxuan Liu:
Learning to Reason with Autoregressive In-Context Distillation. - Zihan Wang:
ONLS: Optimal Noise Level Search in Diffusion Autoencoders Without Fine-Tuning. - Yueqian Lin, Jingyang Zhang, Yiran Chen, Hai Li:
SD-NAE: Generating Natural Adversarial Examples with Stable Diffusion. - Juhwan Choi, YoungBin Kim:
Adverb Is the Key: Simple Text Data Augmentation with Adverb Deletion. - Jungyeul Park, Mengyang Qiu:
Frustratingly Simple Prompting-based Text Denoising. - Navdeep Kumar, Ilnura Usmanova, Kfir Yehuda Levy, Shie Mannor:
Towards Faster Global Convergence of Robust Policy Gradient Methods. - Navdeep Kumar, Kaixin Wang, Utkarsh Pratiush, Kfir Yehuda Levy, Shie Mannor:
Policy Gradient for Reinforcement Learning with General Utilities.
Invite to archive
- Ji-Eun Jung:
Investigating Representations for Vision And Touch in Contact Rich Robot Scooping Tasks. - Xunzhu Tang, Yewei Song, Haoye Tian, Zhenghan Chen, Jacques Klein, Tegawendé F. Bissyandé:
Semantic Patch Embedding for Security Detection: A Fine-to-Coarse Grained Approach. - Krrish Chawla, Mario DePavia, Aryan Sahai, Brando Miranda:
A Systematic Study of the Role of Data Quality and Alignment for Fine-tuning LLMs for Enhanced Autoformalization. - Sayed Sajad Hashemi, Michael Guerzhoy, Noah H. Paulson:
Toward Learning Latent-Variable Representations of Microstructures by Optimizing in Spatial Statistics Space. - Thanh-Thien Le, Linh The Nguyen, Dat Quoc Nguyen:
PhoWhisper: Automatic Speech Recognition for Vietnamese. - Anupam Gupta, Pabitra Mitra:
NIRo: A Metric to capture non-iid robustness for Federated Learning Algorithms. - Zhenglong Wu, Qi Qi, Zirui Zhuang, Haifeng Sun, Jingyu Wang:
Pre-Tokenization of Numbers for Large Language Models. - Joze M. Rozanec, Beno Sircelj, Michael Cochez, Gregor Leban:
Back to the Future: predicting causal relationships influencing oil prices. - Marek Dedic, Lukás Bajer, Pavel Procházka, Martin Holena:
Balancing performance and complexity with adaptive graph coarsening. - Rafik Hachana:
Probing the Hidden Layers of a Music Generating Language Model. - Aoife Igoe, Arindam Biswas, Biswajit Basu:
A Study on Polarity distributions for Network Learning. - Ashrya Agrawal, Priyanshi Shah, Sourabh Prakash:
Layered insights into Pyramid feature fusion architecture for SSL. - Deeksha Aggarwal, Yash Mittal, Uttam Kumar:
Advancing Image Classification through Parameter-Efficient Fine-Tuning: A Study on LoRA with Plant Disease Detection Datasets. - Paul Kapust, Monika Kwiatkowski, Olaf Hellwich, Patrik Reiske:
Exploring Dimensional Collapse in Self-Supervised Video Representation Learning. - Suryam Arnav Kalra, Pabitra Mitra, Arindam Biswas, Biswajit Basu:
Graph Expansion in Pruned Recurrent Neural Network Layers Preserves Performance. - Jingjing Zheng, Yankai Cao:
Bayesian-Driven Learning of A New Weighted Tensor Norm for Tensor Recovery. - Vatsal Baherwani, Joseph James Vincent:
Racial and Gender Stereotypes Encoded Into CLIP Representations. - Danil Afonchikov, Elena Kornaeva, Irina Makovik, Alexey Kornaev:
Native machine learning for noisy microscopic data processing. - Tong Zhao, Neil Shah, Elham Ghazizadeh:
Learning from Graphs Beyond Message Passing Neural Networks. - Hshmat Sahak:
Fusing Vision and Language Models to Generate Sequence of Recipe Images from Steps. - Rui Hao, Weikai Xie:
Autonomous Generation of Innovative Content by Multi-Agent System. - Gholamali Aminian, Amirhossein Bagheri, Radmehr Karimian, Mahyar JafariNodeh, Mohammad Hossein Yassaee:
Semi-supervised Learning under Self-training via $f$-Divergence. - NohMyongSung, Cho Ung Hui:
Ai Gen ASSISTment: Analyzing the Effectiveness of Generative AI Data Amplification for Dkt. - Zhicheng Du, Zhaotian Xie, Yan Tong, Peiwu Qin:
LAMPER: LanguAge Model and Prompt EngineeRing for zero-shot time series classification. - Zhaoyan Lyu, Gholamali Aminian, Miguel R. D. Rodrigues:
Synthetic Labeling: A Novel Approach to Advancing Few-Shot Learning. - Ilya Pershin, Dmitrii Tumakov:
Generation of a random self-similarity curve. - Megan Su, Yuwei Bao:
User Modeling Challenges in Interactive AI Assistant Systems. - Chandan Kumar, Ali Jannesari, Matthew J. Darr:
Discerning Self-supervised Learning and Weakly Supervised Learning. - Hadjer Benmeziane:
A Pre-Search Evaluation Framework for Assessing Search Space Complexity. - Simon Böhi, Shkurta Gashi:
Large Language Models for Wearable Data Analysis and Interpretation. - Yuqing Shang, Qiming Wu, Siqi Li, Di Miao:
Empirical Evaluations of Personalized Federated Learning on Heterogeneous Electronic Health Records. - Daniel Netzl:
Beyond Time: Accurately Estimating the Fair Value of Stocks with Machine Learning and Fundamental Data. - Sumit Soman, Sujoy Roychowdhury:
Observations on Building RAG Systems for Technical Documents. - Rishi Gupta, Vaibhav Kumar:
Sound Classification in Indian Cities Using Multi-Label Data and Transfer Learning. - Behraj Khan, Behroz Mirza, Tahir Syed:
Causal Covariate Shift Correction using Fisher information penalty. - Lingyi Yang:
Q-Learning as a montone scheme. - Zhenwei Dai, Chen Luo, Zhen Li, Xianfeng Tang, Hanqing Lu, Rahul Goutam, Haiyang Zhang:
RA-NER: Retrieval augmented NER for knowledge intensive named entity recognition. - Hruturaj Dhake, Akshay Agarwal:
On the Robustness of Drug Abuse Face Classification. - Rubing Xue, Jiaming Pei, Lukun Wang:
Federated Learning on Small Batch Sizes via Batch Renormalization. - Debolina Paul, Saptarshi Chakraborty, Swagatam Das:
t-Divergence: A New Divergence Measure with Application to Robust Statistics & Clustering. - Pratik Pal, Priyanshu Kumar Rai:
Stacking/Ensemble Model for Smartphone-Based Human Activity Recognition using Feature Engineering. - Dor Tsur, Haim H. Permuter:
Visualizing Information Conservation and Decomposition via the Information Matrix. - Qiming Wu, Siqi Li, Di Miao, Yuqing Shang, Xin Li, Nan Liu:
Evaluating the Efficacy of Federated Scoring Systems with Heterogeneous Electronic Health Records. - Anumanchi Agastya Sai Ram Likhit, Divyansh Tripathi, Akshay Agarwal:
A Novel Sector-Based Algorithm for an Optimized Star-Galaxy Classification. - Daniele Rege Cambrin, Paolo Garza:
Paraphrase Loss for Abstractive Summarization. - Boris Kraychev, Ensiye Kiyamousavi:
Exo-Spacetimeformer: Time Series Prediction with External Forecast Integration. - Julian Strohmayer, Martin Kampel:
WiFi CSI-based Long-Range Person Localization Using Directional Antennas. - Wenjie Shu, Zien Zhang:
DDA: A dual-domain attention plug-and-play prior for pansharpening. - Eric Hanchen Jiang, Andrew Lizarraga:
SDSRA: A Skill-Driven Skill-Recombination Algorithm for Efficient Policy Learning. - Jingyu Hu, Mengnan Du:
Enhancing Fairness in In-Context Learning: Prioritizing Minority Samples in Demonstrations. - Jiaming Pei, Haotian Wu:
Entropy-aided prompt Federated learning. - Wenqian Li, Shuran Fu, Yan Pang:
Distributionally Robust Federated Learning with Wasserstein Barycenter. - Sankarshanaa Sagaram, Laven Srivastava, Krish Didwania, Aditya Kasliwal, Pallavi Kailas, Ujjwal Verma:
Solar Panel Segmentation: Self-Supervised Learning Solutions for Imperfect Datasets. - Karen Sargsyan:
Combinatorial CNNs for words. - Yupu Yao:
Generalize Neural Network Through Smooth Hypothesis Function. - Evgenii Pishchik:
Even a single simple augmentation with Self-Supervised Learning can be helpful for the downstream tasks.
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