Domain Adaptation papers, 2023–2026

Key findings

• Domain Adaptation went from 174 papers in 2023 to 263 in 2026, roughly 1.5x in three years.
• CVPR publishes the most Domain Adaptation work: 268 papers from 2023 to 2026, 31% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 7 in 2023 to 38 in 2026.
• Among the 5 topics under Meta-Learning and Transfer, it ranks #3 by 2026 paper count; the fastest grower in the group, Foundation Model Adaptation, is up 3.8x versus 1.5x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026A Dual-Domain Vision Transformer with Spectral Positional Bias
• ICML 2026Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
• ICLR 2026Bayesian Evidence-Driven Prototype Evolution for Federated Domain Adaptation
• CVPR 2026Anatomical Domain Shifts Test-time Heterogeneous Adaptation for 3D Human Pose
• NeurIPS 20253DPE-Gaze:Unlocking the Potential of 3D Facial Priors for Generalized Gaze Estimation
• ICML 2025A General Representation-Based Approach to Multi-Source Domain Adaptation
• ICLR 2025Adaptive Energy Alignment for Accelerating Test-Time Adaptation
• CVPR 2025A4A: Adapter for Adapter Transfer via All-for-All Mapping for Cross-Architecture Models
• NeurIPS 2024A Cross-Domain Benchmark for Active Learning
• ICML 2024Batch Singular Value Polarization and Weighted Semantic Augmentation for Universal Domain Adaptation
• ICLR 2024Adapting Large Language Models via Reading Comprehension
• CVPR 2024Day-Night Cross-domain Vehicle Re-identification
• NeurIPS 2023(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy
• ICML 2023In Search for a Generalizable Method for Source Free Domain Adaptation
• ICLR 2023Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
• CVPR 2023A New Benchmark: On the Utility of Synthetic Data With Blender for Bare Supervised Learning and Downstream Domain Adaptation
• NeurIPS 2026A unified pairwise distribution matching framework for graph domain adaptation under structure shift
• ICML 2026Content-Style Identification via Differential Independence
• ICLR 2026Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection
• CVPR 2026Bridge Basis-Driven Causal Inference Marries VFMs for Domain Generalization

All Domain Adaptation papers

866 papers, page 3 of 18

101. ICLR 2026MoSA: Mosaic Shared Adaptation of Large Language Models
102. ICLR 2026NEO — No-Optimization Test-Time Adaptation through Latent Re-Centering
103. ICLR 2026PARD: Accelerating LLM Inference with Low‑Cost PARallel Draft Model Adaptation
104. ICLR 2026PAS: Estimating the target accuracy before domain adaptation
105. ICLR 2026Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method
106. ICLR 2026Prior-free Tabular Test-time Adaptation
107. ICLR 2026Reasoning-Driven Multimodal LLM for Domain Generalization
108. ICLR 2026S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion
109. ICLR 2026SAE as a Crystal Ball: Interpretable Features Predict Cross-domain Transferability of LLMs without Training
110. ICLR 2026SAGA: Structural Aggregation Guided Alignment with Dynamic View and Neighborhood Order Selection for Multiview Graph Domain Adaptation
111. ICLR 2026Test-Time Adaptation without Source Data for Out-of-Domain Bioactivity Prediction
112. ICLR 2026TRAC: Tensor-Train based Across-layer Compression for Parameter-Efficient Fine-Tuning
113. ICLR 2026TRIDENT: Cross-Domain Trajectory Spatio-Temporal Representation via Distance-Preserving Triplet Learning
114. ICLR 2026Unlearning during Training: Domain-Specific Gradient Ascent for Domain Generalization
115. ICLR 2026VeriTrail: Closed-Domain Hallucination Detection with Traceability
116. ICLR 2026XIL: Cross-Expanding Incremental Learning
117. ICML 2026AvAtar: Learning to Align via Active Optimal Transport
118. ICML 2026Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings
119. ICML 2026BioFormer: Rethinking Cross-Subject Generalization via Spectral Structural Alignment in Biomedical Time-Series
120. ICML 2026Breaking the Scale Barrier: One-Shot Knowledge Transfer via Frequency Transform
121. ICML 2026CELL: A Causal Perspective for Fairness-aware Graph Adaptation
122. ICML 2026COBRA: Contribution-Based Bayesian Rank Allocation for Parameter-Efficient Fine-Tuning
123. ICML 2026Content-Style Identification via Differential Independence
124. ICML 2026DADP: Domain Adaptive Diffusion Policy
125. ICML 2026Diffract: Spectral View of LLM Domain Adaptation
126. ICML 2026Discretized Density-Guided Source-Free Domain Adaptation for Regression
127. ICML 2026Domain Adaptation with Adaptive $f$-Divergence: Tighter Variational Representation and Generalization Bounds
128. ICML 2026Domain Adaptive Object Detection via Dynamic Causal Refinement
129. ICML 2026Domain Transfer Becomes Identifiable via a Single Alignment
130. ICML 2026Domain-Shift-Aware Conformal Prediction for Large Language Models
131. ICML 2026DomED: Redesigning Ensemble Distillation for Domain Generalization
132. ICML 2026Energy-Structured Low-Rank Adaptation for Continual Learning
133. ICML 2026Entangled No More: Multi-Domain Decoupling for Robust Dynamic Graph Neural Networks
134. ICML 2026Estimating Continuous Treatment Effects with Two-Stage Kernel Ridge Regression
135. ICML 2026Exploring Accurate and Transparent Domain Adaptation in Predictive Healthcare via Concept-Grounded Orthogonal Inference
136. ICML 2026Federated Manifold Learning (FML): Tackling Domain Heterogeneity with Structural Knowledge Transfer
137. ICML 2026FiSeR: Fine-Grained Source Representations for Cross-Domain AI Image Detection
138. ICML 2026Geometric Rate–Distortion Invariance for Domain Generalization
139. ICML 2026GP2F: Cross-Domain Graph Prompting with Adaptive Fusion of Pre-trained Graph Neural Networks
140. ICML 2026GR-LoRA: Gradient-Recycling Low-Rank Adaptation for Class-Incremental Learning
141. ICML 2026Hedging on the Frontier: Learning New Tasks with Few Samples
142. ICML 2026HEDP: A Hybrid Energy-Distance Prompt-based Framework for Domain Incremental Learning
143. ICML 2026Identifying dependent components from multi-domain linear mixtures
144. ICML 2026Improving CLIP Adaptation by Breaking Tail Alignment for Source-Free Cross-Domain Few-Shot Learning
145. ICML 2026Incorporating Importance Weighting in Optimal Transport Based Domain Alignment
146. ICML 2026Learning the ESG Geometry with Domain Aware Language Models
147. ICML 2026LoRA-DA: Data-Aware Initialization for Low-Rank Adaptation via Asymptotic Analysis
148. ICML 2026MDGMIX: Boundary-Aware Subgraph Mixing for Multi-Domain Graph Pre-Training
149. ICML 2026Mining Useful General Data for Low-Resource Domain Adaptation
150. ICML 2026Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains

FAQ

How many Domain Adaptation papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

866 in total: 174 in 2023, 209 in 2024, 220 in 2025, 263 in 2026.

How many Domain Adaptation papers are at NeurIPS 2026?

NeurIPS 2026 has 78 Domain Adaptation papers, versus 81 the year before.

How many Domain Adaptation papers are at ICLR 2026?

ICLR 2026 has 46 Domain Adaptation papers, versus 45 the year before.

How many Domain Adaptation papers are at ICML 2026?

ICML 2026 has 69 Domain Adaptation papers, versus 48 the year before.

How many Domain Adaptation papers are at CVPR 2026?

CVPR 2026 has 70 Domain Adaptation papers, versus 46 the year before.

Which conference publishes the most Domain Adaptation papers?

CVPR, with 268 papers from 2023 to 2026.