conftrace_

selection bia

55 papers

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Co-occurring keywords

causal inference (1630) large language model (13587) bias mitigation (500) treatment effect (134) recommender system (534) observational datum (109) heterogeneous treatment effect (50) graphical model (864) multi-armed bandit (1098) causal discovery (460)

Papers

Jump-teaching: Combating Sample Selection Bias via Temporal Disagreement AAAI 2026
Best Arm Identification with Biased Contexts AAAI 2026
Debiased Cognitive Diagnosis: A Contrastive Counterfactual Modeling Method via Variational Autoencoder AAAI 2026
Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO ACL 2026
Benchmarking and Mitigating MCQA Selection Bias of Large Vision-Language Models EMNLP 2025
Quantifying and Mitigating Selection Bias in LLMs: A Transferable LoRA Fine-Tuning and Efficient Majority Voting Approach AACL 2025
CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-Judges ACL 2025
Mitigating Selection Bias with Node Pruning and Auxiliary Options ACL 2025
Addressing Blind Guessing: Calibration of Selection Bias in Multiple-Choice Question Answering by Video Language Models ACL 2025
Quantifying and Mitigating Selection Bias in LLMs: A Transferable LoRA Fine-Tuning and Efficient Majority Voting Approach IJCNLP 2025
Unveiling Selection Biases: Exploring Order and Token Sensitivity in Large Language Models ACL 2024
Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach AAAI 2024
DiffPO: A causal diffusion model for learning distributions of potential outcomes NIPS 2024
Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation NIPS 2024
Critical Gap Between Generalization Error and Empirical Error in Active Learning WACV 2024
Unveiling the Bias Impact on Symmetric Moral Consistency of Large Language Models NIPS 2024
Strengthened Symbol Binding Makes Large Language Models Reliable Multiple-Choice Selectors ACL 2024
Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms ICML 2023
PUe: Biased Positive-Unlabeled Learning Enhancement by Causal Inference NIPS 2023
Discriminative-Invariant Representation Learning for Unbiased Recommendation IJCAI 2023
Correcting for selection bias and missing response in regression using privileged information UAI 2023
Approximate Post-Selective Inference for Regression with the Group LASSO JMLR 2023
Improving Conversational Recommendation Systems via Bias Analysis and Language-Model-Enhanced Data Augmentation EMNLP 2023
Identifying Selection Bias from Observational Data AAAI 2023
Towards Balanced Representation Learning for Credit Policy Evaluation AISTATS 2023