ICLR 2025 Conference Submissions

Towards Robust Evaluation of Protein Generative Models: A Systematic Analysis of Metrics
Pavel Strashnov, Andrey Shevtsov, Viacheslav Meshchaninov, Maria Ivanova, Fedor Nikolaev, Olga Kardymon, Dmitry Vetrov
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Oracle efficient truncated statistics
Konstantinos Karatapanis, Vasilis Kontonis, Christos Tzamos
- Published: 22 Jan 2025, Last Modified: 02 Apr 2025
- ICLR 2025 Poster
- Readers: Everyone
RedHat: Towards Reducing Hallucination in Essay Critiques with Large Language Models
Andrew Zhuoer Feng, Cunxiang Wang, Bosi Wen, Boqun Kou, Haohan Chi, Yu Luo, Lin Fan, Xiaotao Gu, Jie Tang, Hongning Wang, Minlie Huang
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Drop-Upcycling: Training Sparse Mixture of Experts with Partial Re-initialization
Taishi Nakamura, Takuya Akiba, Kazuki Fujii, Yusuke Oda, Rio Yokota, Jun Suzuki
- Published: 22 Jan 2025, Last Modified: 15 Mar 2025
- ICLR 2025 Poster
- Readers: Everyone
DiRaGNN: Attention-Enhanced Entity Ranking for Sparse Graph Networks
Fiza Husain, Anjaly Parayil, Ayush Choure, Rujia Wang, Chetan Bansal
- 28 Sept 2024 (modified: 22 Nov 2024)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Complete multi-modal metric learning for multi-modal sarcasm detection
Jiecheng Zhang, C.L.Philip Chen, Shuzhen Li, Tong Zhang
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Less is More: Stealthy and Adaptive Clean-Image Backdoor Attacks with Few Poisoned
Binyan Xu, Fan YANG, Di Tang, Xilin Dai, Kehuan Zhang
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
PARSE-Ego4D: Personal Action Recommendation Suggestions for Ego-Centric Videos
Steven Abreu, Tiffany D Do, Karan Ahuja, Eric J Gonzalez, Lee Payne, Daniel McDuff, Mar Gonzalez-Franco
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Black-Box Detection of Language Model Watermarks
Thibaud Gloaguen, Nikola Jovanović, Robin Staab, Martin Vechev
- Published: 22 Jan 2025, Last Modified: 28 Feb 2025
- ICLR 2025 Poster
- Readers: Everyone
FredNormer: Frequency Domain Normalization for Non-stationary Time Series Forecasting
Xihao Piao, Zheng Chen, Yushun Dong, Yasuko Matsubara, Yasushi Sakurai
- 28 Sept 2024 (modified: 17 Nov 2024)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
ProAdvPrompter: A Two-Stage Journey to Effective Adversarial Prompting for LLMs
Hao Di, Tong He, Haishan Ye, Yinghui Huang, Xiangyu Chang, Guang Dai, Ivor Tsang
- Published: 22 Jan 2025, Last Modified: 02 Mar 2025
- ICLR 2025 Poster
- Readers: Everyone
Commute Your Domains: Trajectory Optimality Criterion for Multi-Domain Learning
Alexey Rukhovich, Alexander Podolskiy, Irina Piontkovskaya
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
BALSA: Benchmarking Active Learning Strategies for Autonomous laboratories
Po-Yen Tung, Yangtao Chen, Peng Bo, Hao Zhang, Wenjie Du, Stefan Bauer, Ye Wei
- 28 Sept 2024 (modified: 23 Jan 2025)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Robust Heterogeneous Treatment Effect Estimation under Covariate Perturbation
Zhenlei Wang, Haoxuan Li, Haoxiang Wang, Guangyi Chen, Xu Chen, Peng Cui, Kun Zhang
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
GFLAgent: Green Federated Learning Agent for Alleviating Heterogeneity
Hefeng Zhou, Yuanbin WANG, Kailai Li, Jiong Lou, Jie LI
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Ward: Provable RAG Dataset Inference via LLM Watermarks
Nikola Jovanović, Robin Staab, Maximilian Baader, Martin Vechev
- Published: 22 Jan 2025, Last Modified: 25 Feb 2025
- ICLR 2025 Poster
- Readers: Everyone
From Imitation to Introspection: Probing Self-Consciousness in Language Models
Sirui Chen, Shu Yu, Shengjie Zhao, Chaochao Lu
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Multimodal LLM-guided Query Optimization for Visual-Language Retrieval
GuangHao Meng, Tao Dai, Letian Zhang, Jieming Zhu, Jinpeng Wang, Qing Li, Yong Jiang
- 28 Sept 2024 (modified: 03 Dec 2024)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Diffusion on language model encodings for protein sequence generation
Viacheslav Meshchaninov, Pavel Strashnov, Andrey Shevtsov, Fedor Nikolaev, Nikita Ivanisenko, Olga Kardymon, Dmitry Vetrov
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
ToG-I: Progressively Instructed Knowledge Graph-based Large Language Model Reasoning
Minghan Zhang, Zhen Yang, Hongsheng Wu, Yongxing Lin, Jie Chen, Zhen Duan, Shu Zhao
- 28 Sept 2024 (modified: 22 Jan 2025)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Black-Box Adversarial Attacks on LLM-Based Code Completion
Slobodan Jenko, Jingxuan He, Niels Mündler, Mark Vero, Martin Vechev
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Rethinking MUSHRA: Addressing Modern Challenges in Text-to-Speech Evaluation
Praveen Srinivasa Varadhan, amogh gulati, Ashwin Sankar, Anirudh Gupta, Anirudh Mukherjee, Shiva Kumar Marepally, Srija Anand, Ankur Bhatia, Saloni Jaju, Suvrat Bhooshan, Mitesh M Khapra
- 28 Sept 2024 (modified: 29 Nov 2024)
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Scaling Laws for Task-Optimized Models of the Primate Visual Ventral Stream
Abdulkadir Gokce, Martin Schrimpf
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
Cayley Maze: Universal Open-Ended Reinforcement Learning Environment
Artsiom Ranchynski, Łukasz Kuciński
- 28 Sept 2024 (modified: 05 Feb 2025)
- Submitted to ICLR 2025
- Readers: Everyone
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen, Vincent Guigue, Alberto Lumbreras, Laure Soulier, Patrick Gallinari
- Published: 22 Jan 2025, Last Modified: 14 Mar 2025
- ICLR 2025 Poster
- Readers: Everyone