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
Accurate and Efficient Singular Value Decomposition For LLMs via Decay-aware Rank Allocation and Feature-Preserved Weight Update Singular Value Decomposition (SVD) provides a hardware-agnostic and effective paradigm for compressing and accelerating Large Language Models (LLMs) by decomposing and truncating weight matrices, foll... 5.00 12% See Reviews View AI Dashboard
Soft Instruction De-escalation Defense Large Language Models (LLMs) are increasingly deployed in agentic systems that interact with an external environment; this makes them susceptible to prompt injections when dealing with untrusted data.... 6.00 8% See Reviews View AI Dashboard
DAG-MoE: From Simple Mixture to Structural Aggregation in Mixture-of-Experts Mixture-of-Experts (MoE) models have become a leading approach for decoupling parameter count from computational cost in large language models. Despite significant progress, effectively scaling MoE pe... 3.60 0% See Reviews View AI Dashboard
Token-Guard: Towards Token-Level Hallucination Control via Self-Checking Decoding Large Language Models (LLMs) often hallucinate, generating content inconsistent with the input. Retrieval-Augmented Generation (RAG) and Reinforcement Learning with Human Feedback (RLHF) can mitigate ... 5.50 34% See Reviews View AI Dashboard
Sampling On Metric Graphs Metric graphs are structures obtained by associating edges in a standard graph with segments of the real line and gluing these segments at the vertices of the graph. The resulting structure has a natu... 4.50 6% See Reviews View AI Dashboard
Enabling Agents to Communicate Entirely in Latent Space While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling rich, internal latent states into discrete tokens in... 3.33 0% See Reviews View AI Dashboard
Mixing Configurations for Downstream Prediction Humans possess an innate ability to group objects by similarity—a cognitive mechanism that clustering algorithms aim to emulate. Recent advances in community detection have enabled the discovery of co... 3.00 2% See Reviews View AI Dashboard
Urban Socio-Semantic Segmentation with Vision-Language Reasoning As hubs of human activity, urban surfaces consist of a wealth of semantic entities. Segmenting these various entities from satellite imagery is crucial for a range of downstream applications. Current ... 4.00 0% See Reviews View AI Dashboard
PROBE: Probing Residual Concept Capacity in Erased Text-to-Video Models Text-to-video (T2V) diffusion models have achieved remarkable progress in generating temporally coherent, high-quality videos. However, their ability to generate sensitive or undesired concepts has ra... 3.00 62% See Reviews View AI Dashboard
Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective Reinforcement Learning (RL) has proven highly effective for autoregressive language models, but adapting these methods to diffusion large language models (dLLMs) presents fundamental challenges. The c... 5.50 21% See Reviews View AI Dashboard
Reducing Hallucinations in Generative Models through Truncated Statistics Hallucinations—where generative models produce invalid or nonsensical outputs—remain a critical challenge for reliable deployment. We present the first computationally and query-efficient algorithm th... 5.33 4% See Reviews View AI Dashboard
GazeVLM: Gaze-Guided Vision-Language Models for Efficient and Robust Inference Vision-language models (VLMs) are emerging as a core building block of modern intelligent assistants, enabling real-time human-machine interactions based on natural language and vision. However, the e... 4.00 0% See Reviews View AI Dashboard
GLLP: Graph Learning from Label Proportions Learning from Label Proportion (LLP) is a weakly supervised learning paradigm in which only aggregated label proportions over collections of instances (i.e., bags) are provided, rather than individual... 3.50 3% See Reviews View AI Dashboard
From Conversation to Query Execution: Benchmarking User and Tool Interactions for EHR Database Agents Despite the impressive performance of LLM-powered agents, their adoption for Electronic Health Record (EHR) data access remains limited by the absence of benchmarks that adequately capture real-world ... 4.00 0% See Reviews View AI Dashboard
Blur to Focus Attention in Fine-Grained Visual Recognition Fine-grained visual recognition (FGVR) requires distinguishing categories separated by tiny discriminative cues such as fine textures, part shapes, or color patterns. In typical datasets, discriminati... 3.00 43% See Reviews View AI Dashboard
Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning Continual learning in large language models (LLMs) is prone to catastrophic forgetting, where adapting to new tasks significantly degrades performance on previously learned ones. Existing parameter-ef... 5.00 87% See Reviews View AI Dashboard
Towards Better Branching Policies: Leveraging the Sequential Nature of Branch-and-Bound Tree The branch-and-bound (B\&B) method is a dominant exact algorithm for solving Mixed-Integer Linear Programming problems (MILPs). While recent deep learning approaches have shown promise in learning bra... 5.00 12% See Reviews View AI Dashboard
Interpretable Transformer Regression for Functional and Longitudinal Covariates We consider scalar-on-function prediction from functional covariates that may be measured sparsely and irregularly over time with noise, which is common in longitudinal studies. We propose a dual‑atte... 4.00 4% See Reviews View AI Dashboard
RAPID: An Efficient Reinforcement Learning Algorithm for Small Language Models Reinforcement learning (RL) has emerged as a promising strategy for finetuning small language models (SLMs) to solve targeted tasks such as math and coding. However, RL algorithms tend to be resource-... 1.50 0% See Reviews View AI Dashboard
VLA-IN-THE-LOOP: ONLINE POLICY CORRECTION WITH WORLD MODELS FOR ROBUST ROBOTIC GRASPING Large-scale Vision-Language-Action (VLA) models excel at mapping natural language instructions to robotic action. However, they typically treat actions as terminal outputs with imitation learning ofte... 5.00 52% See Reviews View AI Dashboard
SP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution The state space model (SSM) has garnered significant attention recently due to its exceptional long-range modeling capabilities achieved with linear-time complexity, enabling notable success in effici... 6.00 4% See Reviews View AI Dashboard
Beacon: Thwarting Backdoor Attacks in Cross-Domain Federated Fine-Tuning via Gradient Behavior Decoupling Cross-domain federated fine-tuning (CD-FFT) has emerged as a promising paradigm evolving from traditional federated learning (FL), with better alignment to real-world data distributions and enhanced c... 4.00 29% See Reviews View AI Dashboard
NVE-Adaptor: Novel View Editing Adaptor for Unseen View Consistent 3D Editing 3D editing aims to transform a given 3D structure according to the user's intent. Multi-view consistent 3D editing has been proposed to ensure consistent editing effects across different views of a 3D... 3.50 0% See Reviews View AI Dashboard
PCA Feature Alignment is Sufficient for Building Graph Foundation Models Graph foundation models (GFMs) aim to pretrain graph neural networks (GNNs) that can generalize to new graph datasets in a zero-shot manner, requiring little or no additional training. This goal is ch... 2.00 0% See Reviews View AI Dashboard
The Quest for Generalizable Motion Generation: Data, Model, and Evaluation Despite recent advances in 3D human motion generation (MoGen) on standard benchmarks, existing models still face a fundamental bottleneck in their generalization capability. In contrast, adjacent gene... 5.50 38% See Reviews View AI Dashboard
Demystifying Hybrid Thinking: Can LLMs Truly Switch Between Think and No-Think? Hybrid thinking enables LLMs to switch between reasoning and direct answering, offering a balance between efficiency and reasoning capability. Yet our experiments reveal that current hybrid thinking L... 3.00 0% See Reviews View AI Dashboard
CartoonSing: Unifying Human and Nonhuman Timbres in Singing Generation Singing voice synthesis (SVS) and singing voice conversion (SVC) have achieved remarkable progress in generating natural-sounding human singing. However, existing systems are restricted to human timbr... 2.50 13% See Reviews View AI Dashboard
Real-VAS: a Realworld Video Amodal Segmentation dataset Amodal video object segmentation is fundamentally limited by the absence of datasets that combine real-world complexity with precise ground-truth annotations. To address this, we present Real Video Am... 4.50 22% See Reviews View AI Dashboard
Winformer: Transcending pairwise similarity for time-series generation Time-series generation plays a critical role in data imputation, feature augmentation, domain adaptation, and foundation modeling. However, the cross-domain generation remains a persistent challenge, ... 5.00 0% See Reviews View AI Dashboard
Divide and Conquer Self-Supervised Learning for High-Content Imaging Self-supervised representation learning methods often fail to learn subtle or complex features, which can be dominated by simpler patterns which are much easier to learn. This limitation is particular... 2.50 0% See Reviews View AI Dashboard
Stable and Diverse Strategy Learning via Diffusion-Based Co-Evolution in StarCraft II Combat Effective learning algorithms for agents in multi-agent environments remain a central challenge due to inter-agent dependencies during both training and evaluation. This challenge is amplified by the ... 1.50 16% See Reviews View AI Dashboard
Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation The conditional average treatment effect (CATE) is widely used in personalized medicine to inform therapeutic decisions. However, state-of-the-art methods for CATE estimation (so-called meta-learners)... 5.50 0% See Reviews View AI Dashboard
How Can LLMs Serve as Experts in Malicious Code Detection? A Graph Representation Learning Based Approach Large Language Models (LLMs) excel in code processing yet encounter challenges in malicious code detection, primarily due to their limited ability to capture long-range dependencies within large and c... 5.00 0% See Reviews View AI Dashboard
Breaking Safety Alignment in Large Vision-Language Models via Benign-to-Harmful Optimization Large vision–language models (LVLMs) achieve remarkable multimodal reasoning capabilities but remain vulnerable to jailbreaks. Recent studies show that a single jailbreak image can universally bypass ... 5.50 0% See Reviews View AI Dashboard
MASTARS: Multi-Agent Sequential Trajectory Augmentation with Return-Conditioned Subgoals The performance of offline reinforcement learning (RL) critically depends on the quality and diversity of the offline dataset. While diffusion-based data augmentation for offline RL has shown promise ... 4.00 0% See Reviews View AI Dashboard
Endowing GPT-4 with a Humanoid Body: Building the Bridge Between Off-the-Shelf VLMs and the Physical World In this paper, we explore how to empower general-purpose Vision-Language Models (VLMs) to control humanoid agents. General-purpose VLMs (e.g., GPT-4) exhibit strong open-world generalization, and remo... 5.50 0% See Reviews View AI Dashboard
SoftPose: Learning Soft Attention for Interaction-Aware Multi-Person Image Generation Pose-guided human image generation aims to synthesize images of individuals performing specific actions based on pose conditions and textual descriptions. While current methods achieve promising resul... 4.50 60% See Reviews View AI Dashboard
Imitation Learning for Multi-turn LM Agents via On-policy Expert Corrections A popular paradigm for training LM agents relies on *imitation learning*, fine-tuning on expert trajectories. However, we show that the off-policy nature of imitation learning for multi-turn LM agents... 4.00 0% See Reviews View AI Dashboard
Fleming-R1: Toward Expert-Level Medical Reasoning via Reinforcement Learning While large language models show promise in medical applications, achieving expert-level clinical reasoning remains challenging due to the need for both accurate answers and transparent reasoning proc... 4.00 63% See Reviews View AI Dashboard
Can Data-driven Machine Learning Reach Symbolic-level Logical Reasoning? -- The Limit of the Scaling Law With the qualitative extension of embedding representation and the method of explicit model construction, neural networks may achieve the rigour of symbolic level logic reasoning without training data... 3.50 0% See Reviews View AI Dashboard
Zero-Shot Video Restoration and Enhancement with Assistance of Video Diffusion Models Although diffusion-based zero-shot image restoration and enhancement methods have achieved great success, applying them to video restoration or enhancement will lead to severe temporal flickering. In ... 5.50 0% See Reviews View AI Dashboard
Cell2Text: Multimodal LLM for Generating Single-Cell Descriptions from RNA-Seq Data Single-cell RNA sequencing has transformed biology by enabling the measurement of gene expression at cellular resolution, providing information for cell types, states, and disease contexts. Recently, ... 3.50 37% See Reviews View AI Dashboard
EntryPrune: Neural Network Feature Selection using First Impressions There is an ongoing effort to develop feature selection algorithms to improve interpretability, reduce computational resources, and minimize overfitting in predictive models. Neural networks stand out... 3.00 0% See Reviews View AI Dashboard
CCC: Prompt Evolution for Video Generation via Structured MLLM Feedback Video generation from natural-language prompts has made impressive strides, but current systems frequently misalign outputs with their input descriptions—dropping critical details, hallucinating unint... 3.50 54% See Reviews View AI Dashboard
Measuring Scarcity–Complexity Collision in Language Model Estimation Formal languages are increasingly used to analyze limitations of language–model architectures, via properties of their defining automata (e.g., number of states, transition weights, or out-degree at a... 4.50 0% See Reviews View AI Dashboard
Black-Box Guardrail Reverse-engineering Attack Large language models (LLMs) increasingly employ guardrails to enforce ethical, legal, and application-specific constraints on their outputs. While effective at mitigating harmful or undesirable respo... 3.50 52% See Reviews View AI Dashboard
Rethinking Regularization in Federated Learning: An Initialization Perspective In federated learning, numerous regularization methods have been introduced to alleviate local drift caused by data heterogeneity. While all share the goal of reducing client drift, their effects on c... 4.00 0% See Reviews View AI Dashboard
UEval: A Real-World Benchmark for Unified Multimodal Generation We introduce UEval, a challenging real-world benchmark for multimodal generation of unified models, i.e., models capable of generating both images and text. UEval comprises 1,000 expert-curated prompt... 4.50 0% See Reviews View AI Dashboard
FORCE: Transferable Visual Jailbreaking Attacks via Feature Over-Reliance CorrEction The integration of new modalities enhances the capabilities of multimodal large language models (MLLMs) but also introduces additional vulnerabilities. In particular, simple visual jailbreaking attack... 4.50 0% See Reviews View AI Dashboard
Learning with Local Search MCMC Layers Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing approaches lack theoretical guarantees or fail to perfor... 5.00 0% See Reviews View AI Dashboard
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