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Papers
Autonomous Concept Drift Threshold Determination
AAAI 2026
Breaking the Illusion of Reasoning in Polish LLMs: Quality over Quantity of Thought
EACL 2026
Garbage In, Reasoning Out? Why Benchmark Scores are Unreliable and What to Do About It
EACL 2026
A new framework for evaluating model out-of-distribution generalisation for the biochemical domain
ICLR 2025
A Proactive Reliability Metric for Detecting Failures in Language Model Training
EMNLP 2025
Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance
EMNLP 2025
Beyond Data Quantity: Key Factors Driving Performance in Multilingual Language Models
COLING 2025
Data Laundering: Artificially Boosting Benchmark Results through Knowledge Distillation
ACL 2025
Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based Inference
EMNLP 2025
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
ICML 2025
Enhancing Prediction Performance through Influence Measure
ICLR 2025
Federated Learning at the Forefront of Fairness: A Multifaceted Perspective
IJCAI 2025
Improving Continual Pre-training Through Seamless Data Packing
ACL 2025
Law of the Weakest Link: Cross Capabilities of Large Language Models
ICLR 2025
Leveraging External Knowledge Bases: Analyzing Presentation Methods and Their Impact on Model Performance
NAACL 2025
LNE-Blocking: An Efficient Framework for Contamination Mitigation Evaluation on Large Language Models
EMNLP 2025
MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
ACL 2025
More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
ACL 2025
NeuroReset : LLM Unlearning via Dual Phase Mixed Methodology
SemEval 2025
One Size Fits None: Rethinking Fairness in Medical AI
ACL 2025
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
ICML 2025
Persona-Augmented Benchmarking: Evaluating LLMs Across Diverse Writing Styles
EMNLP 2025
RAP: A Metric for Balancing Repetition and Performance in Open-Source Large Language Models
NAACL 2025
Rationales Are Not Silver Bullets: Measuring the Impact of Rationales on Model Performance and Reliability
ACL 2025
RealBench: A Chinese Multi-image Understanding Benchmark Close to Real-world Scenarios
EMNLP 2025