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
TESSAR: Geometry-Aware Active Regression via Dynamic Voronoi Tessellation Active learning improves training efficiency by selectively querying the most informative samples for labeling. While it naturally fits classification tasks–where informative samples tend to lie near ... 6.67 23% See Reviews View AI Dashboard
Comp-LTL: Temporal Logic Planning via Zero-Shot Policy Composition This work develops a zero-shot mechanism, Comp-LTL, for an agent to satisfy a Linear Temporal Logic (LTL) specification given existing task primitives trained via reinforcement learning (RL). Autonomo... 3.00 0% See Reviews View AI Dashboard
ZSPAPrune: Zero-Shot Prompt-Aware Token Pruning for Vision-Language Models As the capabilities of Vision-Language Models (VLMs) advance, they can process increasingly large inputs, which, unlike in LLMs, generates significant visual token redundancy and leads to prohibitive ... 3.33 22% See Reviews View AI Dashboard
Dig2DIG: Dig into Diffusion Information Gains for Image Fusion Image fusion integrates complementary information from multiple sources to generate more informative results. Recently, the diffusion model, which demonstrates unprecedented generative potential, has ... 4.00 12% See Reviews View AI Dashboard
RainPro-8: An Efficient Deep Learning Model to Estimate Rainfall Probabilities Over 8 Hours We present a deep learning model for high-resolution probabilistic precipitation forecasting over an 8-hour horizon in Europe, overcoming the limitations of radar-only deep learning models with short ... 4.50 0% See Reviews View AI Dashboard
OR-PRM: A Process Reward Model for Algorithmic Problem in Operations Research Large language models (LLMs) with Process Reward Models (PRMs) have shown strong reasoning ability, yet their potential in Operations Research (OR) remains unexplored. We present the first PRM tailore... 5.50 32% See Reviews View AI Dashboard
TEMPFLOW-GRPO: WHEN TIMING MATTERS FOR GRPO IN FLOW MODELS Recent flow matching models for text-to-image generation have achieved remarkable quality, yet their integration with reinforcement learning for human preference alignment remains suboptimal, hinderin... 7.50 31% See Reviews View AI Dashboard
Causal Partial Identification with Data Augmentation We provide a first analysis for using knowledge of symmetries in data generation via data augmentation (DA) transformations for sharpening bounds on causal effects derived from observational data. The... 4.00 3% See Reviews View AI Dashboard
MolecularIQ: Characterizing Chemical Reasoning Capabilities Through Symbolic Verification on Molecular Graphs Large Language Models (LLMs) are increasingly applied to chemistry, tackling tasks such as molecular name conversion, captioning, text-guided generation, and property or reaction prediction. A molecul... 4.00 8% See Reviews View AI Dashboard
CoRGI: GNNs with Convolutional Residual Global Interaction for Lagrangian Simulation Partial differential equations (PDEs) are central to dynamical systems modeling, particularly in hydrodynamics, where traditional solvers often struggle with nonlinearity and computational cost. Lagra... 3.00 5% See Reviews View AI Dashboard
Training Multi-Layer Transformers in Almost Linear Time The computational complexity of the self-attention mechanism in popular transformer architectures poses significant challenges for training and inference, and becomes the bottleneck for long inputs. I... 2.50 0% See Reviews View AI Dashboard
Understanding Federated Unlearning through the Lens of Memorization Federated learning (FL) must support unlearning to meet privacy regulations. However, existing federated unlearning approaches may overlook the overlapping information between the unlearning and retai... 4.67 3% See Reviews View AI Dashboard
XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a structured, semantically coherent context, yielding... 2.50 55% See Reviews View AI Dashboard
DyME: Dynamic Multi-Concept Erasure in Diffusion Models with Bi-Level Orthogonal LoRA Adaptation Text-to-image diffusion models (DMs) inadvertently reproduce copyrighted styles and protected visual concepts, raising legal and ethical concerns. Concept erasure has emerged as a safeguard, aiming to... 2.50 36% See Reviews View AI Dashboard
Unlocking Decoder-LLMs for Text Embedding with Instructions, Soft Supervision and Curriculum Learning Large language models (LLMs) are increasingly used for text embedding, yet most decoder-only architectures remain underexplored for this purpose. We present a unified instruction-based framework that ... 3.00 77% See Reviews View AI Dashboard
Evaluating SAE interpretability without generating explanations Sparse autoencoders (SAEs) and transcoders have become important tools for machine learning interpretability. However, measuring the quality of the features they uncover remains challenging, and there... 3.50 0% See Reviews View AI Dashboard
BEYOND IMITATION: RECOVERING DENSE REWARDS FROM DEMONSTRATIONS Conventionally, supervised fine-tuning (SFT) is treated as a simple imitation learning process that only trains a policy to imitate expert behavior on demonstration datasets. In this work, we challeng... 4.67 4% See Reviews View AI Dashboard
On the Interaction of Compressibility and Adversarial Robustness Modern neural networks are expected to simultaneously satisfy a host of desirable properties: accurate fitting to training data, generalization to unseen inputs, parameter and computational efficiency... 5.50 0% See Reviews View AI Dashboard
LoRAGen: Structure-Aware Weight Space Learning for LoRA Generation The widespread adoption of Low-Rank Adaptation (LoRA) for efficient fine-tuning of large language models has created demand for scalable parameter generation methods that can synthesize adaptation wei... 5.50 3% See Reviews View AI Dashboard
Contrastive Negative Preference Optimization for Machine Unlearning in LLMs During large-scale training on extensive corpora, language models inevitably memorize unwanted data (e.g., private or copyrighted content). While numerous unlearning methods have been proposed—includi... 3.33 0% See Reviews View AI Dashboard
Beyond Pixels: Efficient Dataset Distillation via Sparse Gaussian Representation Dataset distillation has emerged as a promising paradigm that synthesizes compact, informative datasets capable of retaining the knowledge of large-scale counterparts, thereby addressing the substanti... 4.00 0% See Reviews View AI Dashboard
Toward Evaluative Thinking: Meta Policy Optimization with Evolving Reward Models Reward-based alignment methods for large language models (LLMs) face two key limitations: vulnerability to reward hacking, where models exploit flaws in the reward signal; and reliance on brittle, lab... 4.00 12% See Reviews View AI Dashboard
Protein as a Second Language for LLMs Deciphering the function of unseen protein sequences is a fundamental challenge with broad scientific impact, yet most existing methods depend on task-specific adapters or large-scale supervised fine-... 4.00 16% See Reviews View AI Dashboard
GenCape: Structure-Inductive Generative Modeling for Category-Agnostic Pose Estimation Category-agnostic pose estimation (CAPE) aims to localize keypoints on query images from arbitrary categories, using only a few annotated support examples for guidance. Recent approaches either treat ... 6.00 21% See Reviews View AI Dashboard
PD$^{2}$GS: Part-Level Decoupling and Continuous Deformation of Articulated Objects via Gaussian Splatting Articulated objects are ubiquitous and important in robotics, AR/VR, and digital twins. Most self-supervised methods for articulated object modeling reconstruct discrete interaction states and relate ... 6.00 2% See Reviews View AI Dashboard
Building Data Framework and Shifting Perspectives for First-Person Exploration of Social Intelligence in LLMs Social intelligence is built upon three foundational pillars: cognitive, situational, and behavioral intelligence. As Large Language Models (LLMs) are increasingly integrated into our social lives, un... 3.60 0% See Reviews View AI Dashboard
Scene-R1: Video-Grounded Large Language Models for 3D Scene Reasoning without 3D Annotations Currently, utilizing large language models to understand the 3D world is becoming popular. Yet existing 3D‑aware LLMs act as black boxes: they output bounding boxes or textual answers without revealin... 4.00 0% See Reviews View AI Dashboard
HTS-Adapt: A Hybrid Training Strategy with Adaptive Search Region Adjustment for MILPs Mixed Integer Linear Programming (MILP) problems are essential for optimizing complex systems but are NP-hard, posing significant challenges as the problem scale and complexity increase. Recent advanc... 4.50 19% See Reviews View AI Dashboard
Tele-Catch: Adaptive Teleoperation for Dexterous Dynamic 3D Object Catching Teleoperation is a key paradigm for transferring human dexterity to robots, yet most prior work targets objects that are initially static, such as grasping or manipulation. Dynamic object catch, where... 2.50 37% See Reviews View AI Dashboard
MuEdit: A Lightweight yet Effective Multi-task Model Editing Method Large language models (LLMs) are prone to misinterpreting instructions and generating incorrect responses, stimulating the development of model editing methods. Existing model editing methods, however... 5.00 4% See Reviews View AI Dashboard
SortedRL: Accelerating RL Training for LLMs through Online Length-aware Scheduling Scaling reinforcement learning (RL) has shown strong promise for enhancing the reasoning abilities of large language models (LLMs), particularly in tasks requiring long chain-of-thought generation. Ho... 3.50 5% See Reviews View AI Dashboard
SCOUT: Spatial-Aware Continual Scene Understanding and Switch Policy for Embodied Mobile Manipulation Coordinating navigation and manipulation with robust performance is essential for embodied AI in complex indoor environments. To address this, SCOUT (Spatial-Aware Continual Scene Understanding and Sw... 4.00 4% See Reviews View AI Dashboard
Towards Universal Neural Inference Building general-purpose models that can leverage information across diverse datasets remains challenging due to varying schemas, inconsistent semantics, and arbitrary feature orderings in real-world ... 2.50 65% See Reviews View AI Dashboard
H2IL-MBOM: A Hierarchical World Model Integrating Intent and Latent Strategy for Opponent Modeling in Multi-UAV Game In mixed cooperative-competitive scenarios, the uncertain decisions made by agents on both sides not only render learning non-stationary but also pose significant threats to each other's security. Exi... 2.50 0% See Reviews View AI Dashboard
Multimodal Datasets with Controllable Mutual Information We introduce a framework for generating highly multimodal datasets with explicitly calculable mutual information between modalities. This enables the construction of benchmark datasets that provide a ... 2.50 0% See Reviews View AI Dashboard
MemOrb: A Plug-and-Play Verbal-Reinforcement Memory Layer for E-Commerce Customer Service Large Language Model-based agents(LLM-based agents) are increasingly deployed in customer service, yet they often forget across sessions, repeat errors, and lack mechanisms for continual self-improvem... 1.50 24% See Reviews View AI Dashboard
Projected Neural Additive Models as Universal Approximators This article proves that any continuous multi-variable function can be approximated arbitrarily close by a linear combination of single-variable functions of the inputs in a projected space. Using a s... 3.50 0% See Reviews View AI Dashboard
Long-Context Modeling with Dynamic Hierarchical Sparse Attention for On-Device LLMs The quadratic cost of attention hinders the scalability of long-context LLMs, particularly in resource-constrained settings. While attention is known to be often sparse, existing static sparse methods... 4.00 10% See Reviews View AI Dashboard
F4-ITS: Fine-grained Feature Fusion for Food Image-Text Search The proliferation of digital food content has intensified the need for robust and accurate systems capable of fine-grained visual understanding and retrieval. In this work, we address the challenging ... 2.00 4% See Reviews View AI Dashboard
A Unified Cortical Circuit Model with Divisive Normalization and Self-Excitation for Robust Representation and Memory Maintenance Robust information representation and its persistent maintenance are fundamental for higher cognitive functions. Existing models employ distinct neural mechanisms to separately address noise-resistant... 4.50 17% See Reviews View AI Dashboard
Physically Valid Biomolecular Interaction Modeling with Gauss-Seidel Projection Biomolecular interaction modeling has been substantially advanced by foundation models, yet they often produce all-atom structures that violate basic steric feasibility. We address this limitation by ... 5.33 3% See Reviews View AI Dashboard
Emergent Chess Skill Acquisition in Large Language Models We investigate the emergent behaviors of rule comprehension, tactical execution, and strategic competence in transformer-based models trained on algebraic chess notation. To support structured reasoni... 2.50 100% See Reviews View AI Dashboard
UKAT: Uncertainty-aware Kernel Association Test Modern data collection methods routinely provide uncertainty estimates alongside point measurements, yet standard statistical tests typically ignore this valuable information. We introduce \texttt{UKA... 3.00 44% See Reviews View AI Dashboard
EchoMotion: Unified Human Video and Motion Generation via Dual-Modality Diffusion Transformer Video generation models have advanced significantly, yet they still struggle to synthesize complex human movements due to the high degrees of freedom in human articulation. This limitation stems from ... 5.00 7% See Reviews View AI Dashboard
Sculpting User Preferences for Recommendation with Positive-Negative Diffusion Guidance Diffusion models are emerging as a powerful generative paradigm for sequential recommendation, demonstrating a remarkable ability to model complex user-item interaction dynamics. Despite their strong ... 4.00 28% See Reviews View AI Dashboard
Principled Policy Optimization for LLMs via Self-Normalized Importance Sampling Reinforcement Learning from Human Feedback (RLHF) is a key technique for aligning Large Language Models (LLMs) with human preferences. While Proximal Policy Optimization (PPO) is the standard algorith... 5.00 39% See Reviews View AI Dashboard
InverseScope: Scalable Activation Inversion for Interpreting Large Language Models Understanding the internal representations of large language models (LLMs) is a central challenge in interpretability research. Existing feature interpretability methods often rely on strong assumptio... 5.50 13% See Reviews View AI Dashboard
TruncProof: LL(1)-Constrained Generation in Large Language Models with Maximum Token Limitations The generation of machine-readable outputs using LLMs has attracted significant attention. However, existing approaches cannot strictly enforce the maximum number of tokens to be generated. To addres... 5.00 0% See Reviews View AI Dashboard
LONGSHIELD: SCALABLE DISTRIBUTED DIFFERENTIALLY PRIVATE TRAINING FOR LONG-CONTEXT LLMS Large language models excel at in-context learning but can memorize sensitive sequences, enabling membership-inference and extraction attacks. Differential privacy (DP) offers provable protection, yet... 3.00 0% See Reviews View AI Dashboard
Forget Forgetting: Continual Learning in a World of Abundant Memory Continual learning (CL) has traditionally focused on minimizing exemplar memory, a constraint often misaligned with modern systems where GPU time, not storage, is the primary bottleneck. This paper ch... 5.00 26% See Reviews View AI Dashboard
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