Showing 1–20 of 48 results
/ Date/ Name
Oct 8, 2021ViDT: An Efficient and Effective Fully Transformer-based Object DetectorJul 16, 2020Learning from Noisy Labels with Deep Neural Networks: A SurveyAug 27, 2025Towards a Holistic and Automated Evaluation Framework for Multi-Level Comprehension of LLMs in Book-Length ContextsFeb 28, 2025Aligning Extraction and Generation for Robust Retrieval-Augmented GenerationOct 20, 2023Enhancing Abstractiveness of Summarization Models through Calibrated DistillationApr 17, 2022An Extendable, Efficient and Effective Transformer-based Object DetectorSep 30, 2024UniSumEval: Towards Unified, Fine-Grained, Multi-Dimensional Summarization Evaluation for LLMsDec 14, 2024Learning to Verify Summary Facts with Fine-Grained LLM FeedbackOct 17, 2024Learning to Summarize from LLM-generated FeedbackDec 12, 2023Toward Robustness in Multi-label Classification: A Data Augmentation Strategy against Imbalance and NoiseMar 25, 2023Prompt-Guided Transformers for End-to-End Open-Vocabulary Object DetectionJul 1, 2024FineSurE: Fine-grained Summarization Evaluation using LLMsNov 19, 2019Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch SelectionNov 19, 2019How does Early Stopping Help Generalization against Label Noise?Dec 8, 2020Robust Learning by Self-Transition for Handling Noisy LabelsMar 27, 2025ReFeed: Multi-dimensional Summarization Refinement with Reflective Reasoning on FeedbackFeb 6, 2026Completing Missing Annotation: Multi-Agent Debate for Accurate and Scalable Relevant Assessment for IR BenchmarksMay 30, 2022Dataset Condensation via Efficient Synthetic-Data ParameterizationMar 29, 2022Online Continual Learning on a Contaminated Data Stream with Blurry Task BoundariesJul 19, 2022Time Is MattEr: Temporal Self-supervision for Video Transformers