Information Extraction papers, 2023–2026

Key findings

• Information Extraction went from 143 papers in 2023 to 266 in 2026, roughly 1.9x in three years.
• NeurIPS publishes the most Information Extraction work: 287 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 28 in 2026.
• Among the 5 topics under Natural Language, it ranks #3 by 2026 paper count; the fastest grower in the group, Retrieval-Augmented Generation, is up 5.4x versus 1.9x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026$\texttt{bispectrum}$: Selective $G$-Bispectra Made Practical
• ICML 2026AREA: Attribute Extraction and Aggregation for CLIP-Based Class-Incremental Learning
• ICLR 2026An Information-Theoretic Parameter-Free Bayesian Framework for Probing Labeled Dependency Trees from Attention Score
• CVPR 2026ActiveGrasp Information-Guided Active Grasping with Calibrated Energy-based Model
• NeurIPS 2025A Pre-training Framework for Relational Data with Information-theoretic Principles
• ICML 2025A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
• ICLR 2025ADAM: An Embodied Causal Agent in Open-World Environments
• CVPR 2025A Focused Human Body Model for Accurate Anthropometric Measurements Extraction
• NeurIPS 2024TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
• ICML 2024An Information-Theoretic Analysis of In-Context Learning
• ICLR 2024Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
• CVPR 2024Differentiable Information Bottleneck for Deterministic Multi-view Clustering
• NeurIPS 2023A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
• ICML 2023Abstracting Imperfect Information Away from Two-Player Zero-Sum Games
• ICLR 2023A VAE for Transformers with Nonparametric Variational Information Bottleneck
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026An Information-theoretic Framework for Auditing Unfairness in Training Data
• ICML 2026GCIB: Graph Contrastive Information Bottleneck for Multi-Behavior Recommendation
• ICLR 2026Calibrated Information Bottleneck for Trusted Multi-modal Clustering
• CVPR 2026Beyond Whats Shared Recovering Lost Unique Information from Intermediate Layers

All Information Extraction papers

287 papers, page 2 of 6

51. NeurIPS 2026Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
52. NeurIPS 2026MatCurvs: Article Real-Coordinate Curve Extraction for Agent-Ready Materials Reasoning
53. NeurIPS 2026Matrix-Free Natural Gradient via Stochastic Truncated Metrics
54. NeurIPS 2026Mind the Gap: Information Disadvantage as a Learning Signal in Cooperative MARL
55. NeurIPS 2026MIRA: Mutual Information guided calibration for Reliable Test-Time Adaptation
56. NeurIPS 2026No Coin Left Behind: Maximizing Strategic Surplus Against No-Regret Dynamics
57. NeurIPS 2026On Making $SE(2)$-Invariant Networks Optimal
58. NeurIPS 2026On Minimizing Regret in Fixed-Confidence $\varepsilon$-Best Arm Identification
59. NeurIPS 2026On Reparameterizing the Score Function
60. NeurIPS 2026On the Impact of Side-Information in Bandit Learning: More is Not Always Merrier
61. NeurIPS 2026On the Information Loss of Multi-Token Prediction: Origin and Solution
62. NeurIPS 2026Opening the Black Box of Classifier-Free Guidance via Information Bottleneck
63. NeurIPS 2026PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting
64. NeurIPS 2026PANDA: Prior-guided Attentional Dual-path Architecture
65. NeurIPS 2026PatchScout: Thematic Web Data Collection via Information Foraging
66. NeurIPS 2026Pathways of Visual Information Flow in Vision-Language Models
67. NeurIPS 2026PepDDG: Peptide–Protein Binding ΔΔ𝐺 Prediction via Information Channel Decomposition
68. NeurIPS 2026PLACE: Patch-Level Agnostic Concept Extraction
69. NeurIPS 2026PRISM: Prior Relational Information for Self-supervised Modeling to Enhance Solubility OOD Generalization
70. NeurIPS 2026Reading Positional Coupling in Transformers with Diffusion Scores
71. NeurIPS 2026Reasoning as Compression: Unifying Budget Forcing via the Conditional Information Bottleneck
72. NeurIPS 2026Refinement as a Service: Algorithmic Predictor Refinement
73. NeurIPS 2026Reinforcement Learning with Multi-Step Lookahead Information Via Adaptive Batching
74. NeurIPS 2026Retrieval Heads Meet Vision: Uncovering How VLMs Locate and Extract Visual Information
75. NeurIPS 2026Robust Multi-view Clustering against Imperfect Information
76. NeurIPS 2026SAME: Stability-Aware Embedding Extraction in Mixture-of-Experts Language Models
77. NeurIPS 2026SBNO : Schrödinger Bridge Neural Operator for the Forward and Inverse Problems under Missing Information
78. NeurIPS 2026Securing AI Agents with Information-Flow Control
79. NeurIPS 2026Self-Distilled RLVR
80. NeurIPS 2026Selling Information While Being an Interested Party
81. NeurIPS 2026SPATIALEPIBENCH: Benchmarking Spatial Information and Epidemic Priors in Forecasting
82. NeurIPS 2026Spectral Estimation with Deformed Decompression
83. NeurIPS 2026Spectral Geometry of Attention: From Information Routing to Uncertainty
84. NeurIPS 2026Stabilizing RL+Search for Imperfect-Information Extensive-Form Games
85. NeurIPS 2026Submodular Benchmark Selection
86. NeurIPS 2026The Bayesian Learning Rule Beyond KL Geometry
87. NeurIPS 2026The Communication Bottleneck: A Round-Trip Study of Compositional Serialization in Language Models
88. NeurIPS 2026The limbic navigation system as a hierarchical RNN
89. NeurIPS 2026The Text Uncanny Valley: Non-Monotonic Performance Degradation in LLM Information Retrieval
90. NeurIPS 2026The Type Theory of Stationary MDPs: Rare Events and Uncertainty Quantification
91. NeurIPS 2026Theoretical Limits of Language Model Alignment
92. NeurIPS 2026TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
93. NeurIPS 2026Training Language Models to Explain Their Own Computations
94. NeurIPS 2026Transfer Entropy as a Measure of Information Flow in VLMs and LLMs
95. NeurIPS 2026Watermarking Game-Playing Agents in Perfect-Information Extensive-Form Games
96. NeurIPS 2026Why Cancer cfDNA Models Fail on Chronic Disease: A Geometric Information-Theoretic Bound and Its Architectural Implications
97. NeurIPS 2025A Pre-training Framework for Relational Data with Information-theoretic Principles
98. NeurIPS 2025A Semantic Parsing Framework for End-to-End Time Normalization
99. NeurIPS 2025Balanced Active Inference
100. NeurIPS 2025ChemX: A Collection of Chemistry Datasets for Benchmarking Automated Information Extraction

FAQ

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

798 in total: 143 in 2023, 190 in 2024, 199 in 2025, 266 in 2026.

How many Information Extraction papers are at NeurIPS 2026?

NeurIPS 2026 has 96 Information Extraction papers, versus 80 the year before.

How many Information Extraction papers are at ICLR 2026?

ICLR 2026 has 63 Information Extraction papers, versus 50 the year before.

How many Information Extraction papers are at ICML 2026?

ICML 2026 has 74 Information Extraction papers, versus 46 the year before.

How many Information Extraction papers are at CVPR 2026?

CVPR 2026 has 33 Information Extraction papers, versus 23 the year before.

Which conference publishes the most Information Extraction papers?

NeurIPS, with 287 papers from 2023 to 2026.