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
No, of Course I Can! Deeper Fine-Tuning Attacks That Bypass Token-Level Safety Mechanisms Leading language model (LM) providers like OpenAI and Anthopic allow customers to fine-tune frontier LMs for specific use cases. To prevent abuse, these providers apply filters to block fine-tuning on... 5.50 0% See Reviews View AI Dashboard
Prompt-Guided Low-Level Recovery and High-Level Fusion for Incomplete Multimodal Sentiment Analysis Multimodal Sentiment Analysis seeks to understand emotions by combining language, audio, and visual signals, but its real challenge lies in building models that stay robust when one or more modalities... 3.00 64% See Reviews View AI Dashboard
Unleashing Guidance Without Classifiers for Human-Object Interaction Animation Generating realistic human-object interaction (HOI) animations remains challenging because it requires jointly modeling dynamic human actions and diverse object geometries. Prior diffusion-based appro... 4.50 2% See Reviews View AI Dashboard
UNSUPERVISED CONFORMAL INFERENCE: BOOTSTRAPPING AND ALIGNMENT TO CONTROL LLM UNCERTAINTY Deploying black-box LLMs requires managing uncertainty in the absence of token-level probability or true labels. We propose introducing an unsupervised conformal inference framework for generation, w... 2.67 4% See Reviews View AI Dashboard
Physics-Informed Audio-Geometry-Grid Representation Learning for Universal Sound Source Localization Sound source localization (SSL) is a fundamental task for spatial audio understanding, yet most deep neural network-based methods are constrained by fixed array geometries and predefined directional g... 5.33 10% See Reviews View AI Dashboard
Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels We introduce Sparse pretrained Radio Transformer (SpaRTran), an unsupervised representation learning approach based on the concept of compressed sensing for wireless channels. SpaRTran learns embeddin... 3.50 0% See Reviews View AI Dashboard
PhyloTextDiff: Text-Based Discrete Diffusion for Generative Phylogenetic Inference Phylogenetic inference aims to reconstruct the evolutionary relationships among species from DNA sequence data. Despite its long history and broad applications, accurately modeling phylogenetic tree d... 3.00 10% See Reviews View AI Dashboard
Consistent Region-Informed Self-supervised Pretraining Dense prediction tasks such as semantic segmentation require representations that capture both global semantics and local structure. Most self-supervised learning methods prioritise image-level invari... 3.60 27% See Reviews View AI Dashboard
Toward Balanced Continual Learning via Fine-Grained Neuronal Intervention Inspired by Memory Consolidation Continual learning confronts the fundamental stability-plasticity dilemma between preserving previously acquired knowledge and adapting to novel tasks. Existing approaches employ coarse-grained networ... 3.33 21% See Reviews View AI Dashboard
Multimodal Classification via Total Correlation Maximization Multimodal learning integrates data from diverse sensors to effectively harness information from different modalities. However, recent studies reveal that joint learning often overfits certain modalit... 5.50 0% See Reviews View AI Dashboard
ENTER THE VOID: EXPLORING WITH HIGH ENTROPY PLANS Model-based reinforcement learning (MBRL) offers an intuitive way to increase the sample efficiency of model-free RL methods by simultaneously training a world model that learns to predict the future.... 3.50 7% See Reviews View AI Dashboard
Spotlight on Token Perception for Multimodal Reinforcement Learning While Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Vision-Language Models (LVLMs), most existing methods in multimodal reasoning neglect the c... 6.00 18% See Reviews View AI Dashboard
LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners Lifelong learning is essential for intelligent agents operating in dynamic environments. Current large language model (LLM)-based agents, however, remain stateless and unable to accumulate or transfer... 2.00 61% See Reviews View AI Dashboard
Rethinking the Actor-Critic Networks using Hybrid Quantum-Classical Paradigm We present a novel hybrid quantum-classical actor-critic reinforcement learning (RL) model. In the noisy intermediate-scale quantum (NISQ) era, full utilization of qubits is impractical due to resourc... 2.67 4% See Reviews View AI Dashboard
Generalization and Scaling Laws for Mixture-of-Experts Transformers We develop a theory of generalization and scaling for Mixture-of-Experts (MoE) Transformers that cleanly separates \emph{active} per-input capacity from \emph{routing} combinatorics. Conditioning on f... 5.50 25% See Reviews View AI Dashboard
VideoMathQA: Benchmarking Mathematical Reasoning via Multimodal Understanding in Video Mathematical reasoning in real-world video presents a fundamentally different challenge than static images or text. It requires interpreting fine-grained visual information, accurately reading handwri... 5.60 14% See Reviews View AI Dashboard
NTK with Convex Two-Layer ReLU Networks We theoretically analyze a convex variant of two-layer ReLU neural networks and how it relates to the standard formulation. We show that the formulations are equivalent with respect to their output va... 4.50 0% See Reviews View AI Dashboard
Is a Small Matrix Eigendecomposition Sufficient for Spectral Clustering? Spectral clustering has been widely used in clustering tasks due to its effectiveness. However, its key step, eigendecomposition of an $n\times n$ matrix, is computationally expensive for large-scale ... 3.50 0% See Reviews View AI Dashboard
All in One: Unified Pretraining of GUI Agents via Masked Trajectory Prediction Graphical User Interface (GUI) agents are intelligent systems that interact with software applications by perceiving visual elements and taking appropriate actions. Existing studies typically explore ... 3.50 0% See Reviews View AI Dashboard
The Price of Explainability for Kernel $k$-means The explainability of the machine learning model has received increasing attention recently for security and model reliability reasons. Recently, there has been a surge of interest in interpreting the... 3.50 0% See Reviews View AI Dashboard
Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability Neuron identification is a popular tool in mechanistic interpretability, aiming to uncover the human-interpretable concepts represented by individual neurons in deep networks. While algorithms such as... 4.00 0% See Reviews View AI Dashboard
AbBiBench: A Benchmark for Antibody Binding Affinity Maturation and Design We introduce **AbBiBench** (**A**nti**b**ody **Bi**nding **Bench**marking), a benchmarking framework for antibody binding affinity maturation and design. Unlike previous strategies that evaluate antib... 3.00 0% See Reviews View AI Dashboard
Functional Distribution Networks (FDN) Modern probabilistic regressors often remain overconfident under distribution shift. We present Functional Distribution Networks (FDN), an input-conditioned distribution over network weights that indu... 3.00 21% See Reviews View AI Dashboard
Beyond Formula Complexity: Effective Information Criterion Improves Performance and Interpretability for Symbolic Regression Symbolic regression discovers accurate and interpretable formulas to describe given data, thereby providing scientific insights for domain experts and promoting scientific discovery. However, existing... 3.00 0% See Reviews View AI Dashboard
Investigating intra-abstraction policies for non-exact abstraction algorithms One weakness of Monte Carlo Tree Search (MCTS) is its sample efficiency which can be addressed by building and using state and/or action abstractions in parallel to the tree search, such that informat... 3.33 0% See Reviews View AI Dashboard
MTSSRL-MD: Multi-Task Self-Supervised Representation Learning for EEG Signals across Multiple Datasets Electroencephalography (EEG) supports diverse clinical applications. However, effective EEG representation learning remains difficult because scarce label annotations and heterogeneous EEG montages li... 2.00 28% See Reviews View AI Dashboard
Lost at the Beginning of Reasoning Recent advancements in large language models (LLMs) have significantly advanced complex reasoning capabilities, particularly through extended chain-of-thought (CoT) reasoning that incorporates mechani... 3.00 0% See Reviews View AI Dashboard
MoVE: Mixture-of-Vocabulary-Experts for Improved Representation Learning Vocabulary size is a key design choice in transformers, with recent work showing that larger models benefit from larger vocabularies and achieve better performance at the same training cost. Expanding... 5.00 0% See Reviews View AI Dashboard
A Comprehensive Evaluation of Code Language Models for Security Patch Detection Detecting vulnerability-fixing commits (VFCs) is critical for timely security patch deployment, yet advisory databases lag patch releases by a median of 25 days and many fixes never receive advisories... 4.50 5% See Reviews View AI Dashboard
Stopping Computation for Converged Tokens in Masked Diffusion-LM Decoding Masked Diffusion Language Models generate sequences via iterative sampling that progressively unmasks tokens. However, they still recompute the attention and feed-forward blocks for every token positi... 6.00 0% See Reviews View AI Dashboard
Spoken Named Entity Localization as a Dense Prediction task: End-to-end Frame-Wise Entity Detection Precise temporal localization of named entities in speech is crucial for privacy-preserving audio processing. However, prevailing cascaded pipelines propagate transcription errors and end‐to‐end model... 3.50 39% See Reviews View AI Dashboard
A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems The geometry of dynamical systems estimated from trajectory data is a major challenge for machine learning applications. Koopman and transfer operators provide a linear representation of nonlinear dyn... 5.50 0% See Reviews View AI Dashboard
Differential Privacy for Transformer Embeddings with Nonparametric Variational Information Bottleneck We propose a privacy-preserving method for sharing text data by sharing noisy versions of their transformer embeddings. It has been shown that hidden representations learned by deep models can encode ... 3.33 5% See Reviews View AI Dashboard
Developmental Federated Tuning: A Cognitive-Inspired Paradigm for Efficient LLM Adaptation Federated fine-tuning enables Large Language Models (LLMs) to adapt to downstream tasks while preserving data privacy, but its resource-intensive nature limits deployment on edge devices. In this pape... 4.50 28% See Reviews View AI Dashboard
CONSINTBENCH: EVALUATING LANGUAGE MODELS ON REAL-WORLD CONSUMER INTENT UNDERSTAND- ING Understanding human intent is a complex, high-level task for large language models (LLMs), requiring analytical reasoning, contextual interpretation, dynamic information aggregation, and decision-maki... 3.00 4% See Reviews View AI Dashboard
Exploiting Fine-Tuning Structures to Improve Adversarial Transferability on Downstream SAM Combining the Segment Anything Model (SAM) with fine-tuning techniques allows SAM to be effectively adapted to various downstream image segmentation tasks. However, this adaptability introduces new se... 4.50 N/A See Reviews
Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks Nearly one in five adolescents currently live with a diagnosed mental or behavioral health condition, such as anxiety, depression, or conduct disorder, underscoring the urgency of developing accurate ... 3.00 46% See Reviews View AI Dashboard
The Surprising Soupability of Documents in State Space Models We investigate whether hidden states from Structured State Space Models (SSMs) can be merged post hoc to support downstream reasoning. Inspired by model souping, we propose a strategy where documents ... 4.00 39% See Reviews View AI Dashboard
SPILLage: Agentic Oversharing on the Web We present SPILLAGE, a novel framework for analyzing how web agents handle user resources when accomplishing tasks on their behalf across real-world websites. SPILLAGE introduces the problem of Natura... 2.67 13% See Reviews View AI Dashboard
Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning Memory is crucial for enabling agents to tackle complex tasks with temporal and spatial dependencies. While many reinforcement learning (RL) algorithms incorporate memory, the field lacks a universal ... 6.50 28% See Reviews View AI Dashboard
Patronus: Interpretable Diffusion Models with Prototypes Uncovering the opacity of diffusion-based generative models is urgently needed, as their applications continue to expand while their underlying procedures largely remain a black box. With a critical ... 4.50 14% See Reviews View AI Dashboard
Why Is the Counterintuitive Phenomenon of Likelihood Rare in Tabular Anomaly Detection with Deep Generative Models? Deep generative models with tractable and analytically computable likelihoods, exemplified by normalizing flows, offer an effective basis for anomaly detection through likelihood-based scoring. We dem... 3.00 0% See Reviews View AI Dashboard
Variance-Guided Score Regularization for Hallucination Mitigation in Diffusion Models Diffusion models have emerged as the backbone of modern generative AI, powering advances in vision, language, audio and other modalities. Despite their success, they suffer from \emph{hallucinations},... 4.00 0% See Reviews View AI Dashboard
SupCL-GSS: Supervised Contrastive Learning with Guided Sample Selection We present Supervised Contrastive Learning with Guided Sample Selection (SupCL-GSS), that leverages data maps to construct "hard" positives and "hard" negatives for text classification on pre-trained ... 3.50 0% See Reviews View AI Dashboard
Characterizing the Discrete Geometry of ReLU Networks It is well established that ReLU networks define continuous piecewise-linear functions, and that their linear regions are polyhedra in the input space. These regions form a complex that fully partitio... 7.50 0% See Reviews View AI Dashboard
DreamSwapV: Mask-guided Subject Swapping for Any Customized Video Editing With the rapid progress of video generation, demand for customized video editing is surging, where subject swapping constitutes a key component yet remains under-explored. Prevailing swapping approach... 5.50 0% See Reviews View AI Dashboard
TAP: Two-Stage Adaptive Personalization of Multi-task and Multi-Modal Foundation Models in Federated Learning Federated Learning (FL), despite demonstrating impressive capabilities in the training of multiple models in a decentralized manner, has been shown to produce a final model not necessarily well-suited... 4.57 0% See Reviews View AI Dashboard
PanoLAM: Large Avatar Model for Gaussian Full-Head Synthesis from One-shot Unposed Image We present a feed-forward framework for Gaussian full-head synthesis from a single unposed image. Unlike previous work that relies on time-consuming GAN inversion and test-time optimization, our frame... 4.50 0% See Reviews View AI Dashboard
AdaBoN: Adaptive Best-of-$N$ Alignment Recent advances in test-time alignment methods, such as Best-of-$N$ sampling, offer a simple and effective way to steer language models (LMs) toward preferred behaviors using reward models (RM). Howev... 4.50 0% See Reviews View AI Dashboard
P-DROP: Poisson-Based Dropout for Graph Neural Networks Stochastic processes are widely used in machine learning, yet interacting particle systems—a class of stochastic processes—have seen limited application. In this paper, we leverage an idea from classi... 2.50 73% See Reviews View AI Dashboard
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