ICLR 2026 - Submissions

SubmissionsReviews

Submissions

Quantity AI Content: 0-10%10-30%30-50%50-70%70-90%90-100%All
Avg Rating: 0-11-22-33-44-55-66-77-88-99-10All

Summary Statistics

Quantity AI Content Count Avg Rating
0-10% 11864 (61%) 4.36
10-30% 3952 (20%) 4.14
30-50% 1846 (9%) 3.93
50-70% 1026 (5%) 3.75
70-90% 494 (3%) 3.39
90-100% 199 (1%) 2.90
Total 19490 (100%) 4.20
Title Abstract Avg Rating Quantity AI Content Reviews Pangram Dashboard
BEARD: Benchmarking the Adversarial Robustness for Dataset Distillation Dataset Distillation (DD) compresses large-scale datasets into smaller synthesized datasets, enabling efficient model training while preserving high test performance. However, existing DD methods prim... 5.00 55% See Reviews View AI Dashboard
Enabling Your Forensic Detector Know ​How Well​ It Performs on Distorted Samples Generative AI has substantially facilitated realistic image synthesizing, posing great challenges for reliable forensics. When image forensic detectors are deployed in the wild, the inputs usually und... 7.00 0% See Reviews View AI Dashboard
Network of Patterns: Time Series Forecasting with Pattern Passing Time series contain diverse pattern information, and many studies have leveraged these patterns to enhance representations for more accurate forecasting. A key challenge lies in how to organize multi-... 2.50 0% See Reviews View AI Dashboard
From Minutes to Days: Scaling Intracranial Speech Decoding with Supervised Pretraining Decoding speech from brain activity has typically relied on limited neural recordings collected during short and highly controlled experiments. Here, we introduce a framework to leverage week-long int... 3.00 0% See Reviews View AI Dashboard
Scalable and Generalizable Autonomous Driving Scene Synthesis Generative modeling has shown remarkable success in vision and language, inspiring research on synthesizing autonomous driving scenes. Existing multi-view synthesis approaches commonly operate in ima... 6.00 9% See Reviews View AI Dashboard
TAVAE: A VAE with Adaptable Priors Explains Contextual Modulation in the Visual Cortex The brain interprets visual information through learned regularities, formalized as performing probabilistic inference under a prior. The visual cortex establishes priors for this inference, some of w... 3.33 0% See Reviews View AI Dashboard
Memorizing Long-tail Data Can Help Generalization Through Composition Deep learning has led researchers to rethink the relationship between memorization and generalization. In many settings, memorization does not hurt generalization due to implicit regularization and ma... 4.67 0% See Reviews View AI Dashboard
SafeRBench: A Comprehensive Benchmark for Safety Assessment of Large Reasoning Models Large Reasoning Models (LRMs) improve answer quality through explicit chain-of-thought, yet this very capability introduces new safety risks: harmful content can be subtly injected, surface gradually,... 3.50 39% See Reviews View AI Dashboard
Deep Global-sense Hard-negative Discriminative Generation Hashing for Cross-modal Retrieval Hard negative generation (HNG) provides valuable signals for deep learning, but existing methods mostly rely on local correlations while neglecting the global geometry of the embedding space. This lim... 6.00 0% See Reviews View AI Dashboard
PANDORA: Diffusion-based Protein Conformation Generation The field of protein design has garnered significant attention in AI for Science (AI4Science). While most existing studies focus on generating native protein structures for applications such as bindin... 2.50 5% See Reviews View AI Dashboard
NAVI: Inductive Alignment for Generalizable Table Representation Learning Effective representation learning for tabular data is critical for downstream tasks such as information retrieval, classification, and missing value imputation. However, existing transformer-based mod... 4.00 10% See Reviews View AI Dashboard
Active Learning for Molecular Conformation Optimization with a Domain-Agnostic Neural Surrogate Oracle Molecular conformation optimization is crucial to computer-aided drug discovery and materials design, yet conventional force-based minimization with physics oracles (e.g., DFT) is prohibitively expens... 2.80 0% See Reviews View AI Dashboard
Discourse-Aware Retrieval-Augmented Generation via Rhetorical Structure Modeling Retrieval-Augmented Generation (RAG) has emerged as an important means for enhancing the performance of large language models (LLMs) in knowledge-intensive tasks. However, most existing RAG strategies... 4.50 24% See Reviews View AI Dashboard
AttentionInfluence: Adopting Attention Head Influence for Weak-to-Strong Pretraining Data Selection Recently, there has been growing interest in collecting reasoning-intensive pretraining data to improve the reasoning ability of LLMs. Prior approaches typically rely on supervised classifiers to iden... 4.00 0% See Reviews View AI Dashboard
Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networks Multivariate Hawkes process provides a powerful framework for modeling temporal dependencies and event-driven interactions in complex systems. While existing methods primarily focus on uncovering caus... 7.00 4% See Reviews View AI Dashboard
Projected Coupled Diffusion for Test-Time Constrained Joint Generation Modifications to test-time sampling have emerged as an important extension to diffusion algorithms, with the goal of biasing the generative process to achieve a given objective without having to retra... 5.00 0% See Reviews View AI Dashboard
DGNet: Self-Supervised Delta2Gamma Multi-Band EEG Representation Learning for Dementia Classification As the global population ages and dementia cases rise, there is an urgent need for effective early diagnosis and monitoring of neurodegenerative diseases. Electroencephalogram (EEG)-based technologies... 1.00 25% See Reviews View AI Dashboard
DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models We study inference-time scaling for diffusion models, where the goal is to adapt a pre-trained model to new target distributions without retraining. Existing guidance-based methods are simple but intr... 6.00 4% See Reviews View AI Dashboard
Confounding Robust Meta-Reinforcement Learning: A Causal Approach Meta-Reinforcement Learning (Meta-RL) focuses on training policies using data collected from a variety of diverse environments. This approach enables the policy to adapt to new settings with only a fe... 4.00 0% See Reviews View AI Dashboard
Parameter-Efficient Reinforcement Learning using Prefix Optimization Reinforcement Learning with Verifiable Rewards (RLVR) is a leading approach for tuning language models on mathematical reasoning tasks. However, it remains unclear whether RLVR's gains stem from genui... 4.50 0% See Reviews View AI Dashboard
SafeDec: Constrained Decoding for Safe Autoregressive Generalist Robot Policies Recent advances in end-to-end, multi-task robot policies based on transformer models have demonstrated impressive generalization to real-world embodied AI tasks. Trained on vast datasets of simulated ... 4.50 0% See Reviews View AI Dashboard
Last-iterate Convergence of ADMM on Multi-affine Quadratic Equality Constrained Problem In this paper, we study a class of non-convex optimization problems known as multi-affine quadratic equality constrained problems, which appear in various applications--from generating feasible force ... 5.50 0% See Reviews View AI Dashboard
Perturbations Matter: Sensitivity-Guided Hallucination Detection in LLMs Hallucination detection is essential for ensuring the reliability of large language models. Internal representation–based methods have emerged as the prevailing direction for detecting hallucinations,... 5.00 3% See Reviews View AI Dashboard
EFRame: Deeper Reasoning via Exploration-Filter-Replay Reinforcement Learning Framework Recent advances in reinforcement learning (RL) have significantly enhanced the reasoning capabilities of large language models (LLMs). Group Relative Policy Optimization (GRPO), a lightweight variant ... 2.50 6% See Reviews View AI Dashboard
OptAgent: Optimizing Query Rewriting for E-commerce via Multi-Agent Simulation Deploying capable and user-aligned LLM-based systems necessitates reliable evaluation. While LLMs excel in verifiable tasks like coding and mathematics, where gold-standard solutions are available, ad... 3.20 0% See Reviews View AI Dashboard
Resolving the Security-Auditability Dilemma with Auditable Latent Chain-of-Thought Reasoning-based methods have emerged to overcome the limitations of 'shallow alignment' by exposing the model's Chain-of-Thought (CoT), enabling auditability through both training-phase supervision an... 4.00 38% See Reviews View AI Dashboard
USDPnet: An Unsupervised Symmetric Deep Framework for Robust Parcellation of Infant Subcortical Nuclei Accurate infant subcortical parcellation is vital for understanding early brain development and neurodevelopmental pathology. However, existing methods suffer from initialization sensitivity, poor bil... 4.50 59% See Reviews View AI Dashboard
DriveE2E: Closed-Loop Benchmark for End-to-End Autonomous Driving through Real-to-Simulation Closed-loop evaluation is increasingly critical for end-to-end autonomous driving. Current closed-loop benchmarks using the CARLA simulator rely on manually configured traffic scenarios, which can div... 4.00 3% See Reviews View AI Dashboard
CausalPlan: Empowering Efficient LLM Multi-Agent Collaboration Through Causality-Driven Planning Large language model (LLM) agents often generate causally invalid plans in collaborative tasks due to their reliance on surface-level correlations rather than grounded causal reasoning. This limitatio... 4.00 7% See Reviews View AI Dashboard
Modeling the Density of Pixel-level Self-supervised Embeddings for Unsupervised Pathology Segmentation in Medical CT Accurate detection of all pathological findings in 3D medical images remains a significant challenge, as supervised models are limited to detecting only the few pathology classes annotated in existing... 6.00 0% See Reviews View AI Dashboard
MedFuse: Multiplicative Embedding Fusion for Irregular Clinical Time Series Clinical time series derived from electronic health records (EHRs) are inherently irregular, with asynchronous sampling, missing values, and heterogeneous feature dynamics. While numerical laboratory ... 1.33 36% See Reviews View AI Dashboard
Dynamic Chunking for End-to-End Hierarchical Sequence Modeling Major progress on language models (LMs) in recent years has largely resulted from moving away from specialized models designed for specific tasks, to general models based on powerful architectures (e.... 6.50 0% See Reviews View AI Dashboard
Identifiability Challenges in Sparse Linear Ordinary Differential Equations Dynamical systems modeling is a core pillar of scientific inquiry across natural and life sciences. Increasingly, dynamical system models are learned from data, rendering identifiability a paramount c... 6.00 0% See Reviews View AI Dashboard
Can Graph Quantization Tokenizer Capture Transferrable Patterns? Graph tokenization aims to convert graph-structured data into discrete representations that can be used in foundation models. Recent methods propose to use vector quantization to map nodes or subgraph... 5.00 10% See Reviews View AI Dashboard
Beyond Score: A Multi-Agent System to Discover Capability and Behavioral Weaknesses in LLMs A key task for researchers working on large language models (LLMs) is to compare the results and behavioral performance of different models, thereby identifying model weaknesses and enabling further m... 4.00 0% See Reviews View AI Dashboard
EGEA-DM: Eigenvalue-Guided Explainable and Accelerated Diffusion Model Diffusion models have achieved remarkable success in generating high-quality data, yet challenges remain in training convergence, interpretability, and fine-grained controllability. Additionally, the ... 4.50 18% See Reviews View AI Dashboard
Exploring Instruction Data Quality for Explainable Image Quality Assessment In recent years, with the rapid development of powerful multimodal large language models (MLLMs), explainable image quality assessment (IQA) has gradually become popular, aiming at providing quality-r... 4.50 0% See Reviews View AI Dashboard
A Geometric Unification of Generative AI with Manifold-Probabilistic Projection Models The foundational premise of generative AI for images is the assumption that images are inherently low-dimensional objects embedded within a high-dimensional space. Additionally, it is often implicitly... 5.00 8% See Reviews View AI Dashboard
Quantum-Inspired Image Encodings for Financial Time-Series Forecasting This study proposes a quantum-inspired methodology that transforms time-series data into complex-valued image representations for prediction. Unlike classical encodings such as the Gramian Angular Fie... 3.33 60% See Reviews View AI Dashboard
Image Embeddings from Social Media: Computer Vision and Human in the Loop Applications for Social Movement Messaging Overview: Social media images are never truly stand-alone, they are grouped to share a specific message sprinkled across a user's feed. Understanding the message of these groups is increasingly impo... 1.50 0% See Reviews View AI Dashboard
SatBench: Satellite Coordination Benchmark Based on Multi-Agent Reinforcement Learning We introduce SatBench, a realistic and flexible benchmark for coordinated satellite tasking in Earth observation (EO) missions. In this setting, multiple satellites potentially in different orbits mus... N/A 62% See Reviews View AI Dashboard
CamPilot: Improving Camera Control in Video Diffusion Model with Efficient Camera Reward Feedback Recent advancements in camera-controlled video diffusion models have significantly improved video-camera alignment and enabled more accurate 3D scene generation, driven by potential downstream applica... 4.50 0% See Reviews View AI Dashboard
Where and Why in Image Forgery: A Benchmark for Joint Localization and Explanation Existing facial forgery detection methods typically focus on binary classification or pixel-level localization, providing little semantic insight into the nature of the manipulation. To address this, ... 3.50 16% See Reviews View AI Dashboard
Linkage-Guided Genetic Variation: Overcoming Operator Blindness in Genetic Algorithms The core bottleneck of Genetic Algorithms is operator blindness: crossover and mutation locations are chosen at random, routinely breaking valuable building blocks. We introduce the Evolving Locus Lin... 2.40 17% See Reviews View AI Dashboard
MIAU: Membership Inference Attack Unlearning Score for Quantifying the Forgetting Quality of Unlearning Methods Machine unlearning aims to adapt the model’s internal representations as if the forget set was never part of training set. In this context, a central challenge lies in accurately evaluating whether fo... 2.50 39% See Reviews View AI Dashboard
PCDVQ: Enhancing Vector Quantization for Large Language Models via Polar Coordinate Decoupling Large Language Models (LLMs) face significant challenges in edge deployment due to their massive parameter scale. Vector Quantization (VQ), a clustering-based quantization method, serves as a prevale... 5.00 0% See Reviews View AI Dashboard
Musculoskeletal simulation of limb movement biomechanics in Drosophila melanogaster Computational models are critical to advance our understanding of how neural, biomechanical, and physical systems interact to orchestrate animal behaviors. Despite the availability of near-complete re... 6.00 3% See Reviews View AI Dashboard
Structure Guided Equation Discovery with Influence-Based Feedback for Large Language Models Large Language Models (LLMs) hold significant promise for scientific discovery, particularly in identifying interpretable, closed-form equations from complex data. However, existing LLM-driven approac... 3.00 81% See Reviews View AI Dashboard
Liars' Bench: Evaluating Deception Detectors for AI Assistants Prior work has studied techniques for detecting when large language models (LLMs) are behaving deceptively. However, deception detection techniques are typically only validated on narrow datasets that... 5.00 0% See Reviews View AI Dashboard
Leveraging Generative Trajectory Mismatch for Cross-Domain Policy Adaptation Transferring policies across domains poses a vital challenge in reinforcement learning, due to the dynamics mismatch between the source and target domains. In this paper, we consider the setting of on... 4.50 5% See Reviews View AI Dashboard
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