Papers
AutoDCWorkflow: LLM-based Data Cleaning Workflow Auto-Generation and Benchmark
Lan Li, Liri Fang, Bertram Ludäscher et al.
StepKE: Stepwise Knowledge Editing for Multi-Hop Question Answering
Jaewook Lee, Dahyun Jung, Heuiseok Lim
Enriching Patent Claim Generation with European Patent Dataset
Lekang Jiang, Chengzu Li, Stefan Goetz
Learning to Instruct: Fine-Tuning a Task-Aware Instruction Optimizer for Black-Box LLMs
Yunzhe Qi, Jinjin Tian, Tianci Liu et al.
MC2: A Minimum-Coverage and Dataset-Agnostic Framework for Compositional Generalization of LLMs on Semantic Parsing
Ziyao Xu, Zhe Yang, Houfeng Wang
ChronoBias: A Benchmark for Evaluating Time-conditional Group Bias in the Time-sensitive Knowledge of Large Language Models
Kyungmin Kim, Youngbin Choi, Hyounghun Kim et al.
Temporal Alignment of Time Sensitive Facts with Activation Engineering
Sanjay Govindan, Maurice Pagnucco, Yang Song
AutoEvolve: Automatically Evolving Queries for Applicable and Scalable Retrieval-Augmented Generation Benchmarking
Ding-Chu Zhang, Xiaowen Zhang, Yue Fei et al.
Forget for Get: A Lightweight Two-phase Gradient Method for Knowledge Editing in Large Language Models
Yanhong Li, Min Yang, Xiping Hu et al.
Decoding in Latent Spaces for Efficient Inference in LLM-based Recommendation
Chengbing Wang, Yang Zhang, Zhicheng Wang et al.
Rotate, Clip, and Partition: Towards W2A4KV4 Quantization by Integrating Rotation and Learnable Non-uniform Quantizer
Euntae Choi, Sumin Song, Woosang Lim et al.
GuiLoMo: Allocating Experts and Ranks for LoRA-MoE via Bilevel Optimization with GuidedSelection Vectors
Xinrong Chen, Hengyuan Zhang, Yingmin Qiu et al.
CoMoE: Contrastive Representation for Mixture-of-Experts in Parameter-Efficient Fine-tuning
Jinyuan Feng, ChaoPeng Wei, Tenghai Qiu et al.
LIFTED: Multimodal Clinical Trial Outcome Prediction via Large Language Models and Mixture-of-Experts
Wenhao Zheng, Liaoyaqi Wang, Dongshen Peng et al.
Towards Reverse Engineering of Language Models: A Survey
Xinpeng Ti, Wentao Ye, Zhifang Zhang et al.
Wait, We Don’t Need to “Wait”! Removing Thinking Tokens Improves Reasoning Efficiency
Chenlong Wang, Yuanning Feng, Dongping Chen et al.
Offloaded Reasoning: Efficient Inference for Large Language Models via Modular Reasoning and Refinement
Ishan Jindal, Jayant Taneja, Badrinath Chandana et al.
Spotlighter: Revisiting Prompt Tuning from a Representative Mining View
Yutong Gao, Maoyuan Shao, Xinyang Huang et al.
HDiff: Confidence-Guided Denoising Diffusion for Robust Hyper-relational Link Prediction
Xiangfeng Luo, Ruoxin Zheng, Jianqiang Huang et al.
Evaluating the Robustness and Accuracy of Text Watermarking Under Real-World Cross-Lingual Manipulations
Mansour Al Ghanim, Jiaqi Xue, Rochana Prih Hastuti et al.
A Survey of Pun Generation: Datasets, Evaluations and Methodologies
Yuchen Su, Yonghua Zhu, Ruofan Wang et al.
Federated Retrieval-Augmented Generation: A Systematic Mapping Study
Abhijit Chakraborty, Chahana Dahal, Vivek Gupta
AdaptMerge: Inference Time Adaptive Visual and Language-Guided Token Merging for Efficient Large Multimodal Models
Zahidul Islam, Mrigank Rochan
Seeing Race, Feeling Bias: Emotion Stereotyping in Multimodal Language Models
Mahammed Kamruzzaman, Amanda Cercas Curry, Alba Cercas Curry et al.