Add hidden_leaderboard.csv for ICLR 2026 sample

hidden_leaderboard.csv

@@ -0,0 +1,51 @@
+openreview_id,frontend_paper_id,venue,title,decision,sample_bucket,primary_area,arxiv_id,submission_date,publication_date,citations_serper,normalized_citations,scores,avg_score,presentations,avg_presentation,soundnesses,avg_soundness,contributions,avg_contribution,confidences,avg_confidence
+0FhrtdKLtD,,ICLR2026,Spatial Mental Modeling from Limited Views,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",,25-09-04,,69,9.857143,2; 6; 6; 6,5.0,1.0; 3.0; 3.0; 3.0,2.5,2.0; 2.0; 3.0; 3.0,2.5,2.0; 3.0; 3.0; 3.0,2.75,3.0; 4.0; 4.0; 3.0,3.5
+1sNhPjqGub,,ICLR2026,Training-free Guidance in Text-to-Video Generation via Multimodal Planning and Structured Noise Initialization,reject,rejected_gt10,"applications to computer vision, audio, language, and other modalities",2504.08641,25-09-19,25-04-11,11,1.833333,4; 8; 2; 4,4.5,3.0; 3.0; 3.0; 3.0,3.0,2.0; 3.0; 2.0; 3.0,2.5,2.0; 3.0; 2.0; 2.0,2.25,5.0; 3.0; 4.0; 4.0,4.0
+SRn1MtMPRq,,ICLR2026,Emergent Coordination in Multi-Agent Language Models,accept (poster),accepted_gt10,generative models,2510.05174,25-09-18,,13,2.166667,6; 4; 4; 6,5.0,2.0; 3.0; 3.0; 3.0,2.75,2.0; 3.0; 3.0; 4.0,3.0,2.0; 3.0; 2.0; 3.0,2.5,4.0; 4.0; 3.0; 3.0,3.5
+tMbmBCfSTz,,ICLR2026,OdysseyBench: Evaluating LLM Agents on Long-Horizon Complex Office Application Workflows,reject,rejected_gt10,datasets and benchmarks,2508.09124,25-09-17,25-08-12,22,3.666667,4; 2; 4; 2,3.0,3.0; 2.0; 2.0; 2.0,2.25,3.0; 2.0; 3.0; 2.0,2.5,2.0; 2.0; 3.0; 2.0,2.25,3.0; 4.0; 3.0; 3.0,3.25
+iiLLQhhrtb,,ICLR2026,Is the Reversal Curse a Binding Problem? Uncovering Limitations of Transformers from a Basic Generalization Failure,accept (poster),accepted_gt10,"unsupervised, self-supervised, semi-supervised, and supervised representation learning",2504.01928,25-09-19,,14,2.333333,4; 6; 6; 4,5.0,3.0; 3.0; 3.0; 2.0,2.75,3.0; 3.0; 3.0; 3.0,3.0,2.0; 3.0; 3.0; 2.0,2.5,3.0; 3.0; 3.0; 3.0,3.0
+t0fU6t3Skw,,ICLR2026,Starjob: Dataset for LLM-Driven Job Shop Scheduling,reject,rejected_gt10,datasets and benchmarks,2503.01877,25-09-19,25-02-26,17,2.833333,4; 2; 2; 2,2.5,2.0; 3.0; 2.0; 2.0,2.25,2.0; 2.0; 2.0; 2.0,2.0,2.0; 2.0; 2.0; 1.0,1.75,4.0; 4.0; 4.0; 4.0,4.0
+nSuJ4OXf0j,,ICLR2026,Mitigating Confounding Effects in Causal Discovery via Time-lagged Backdoor Pathways,reject,rejected_gt10,causal reasoning,,25-09-18,,35,5.833333,2; 4; 2; 2,2.5,2.0; 2.0; 2.0; 2.0,2.0,3.0; 2.0; 1.0; 2.0,2.0,2.0; 2.0; 1.0; 2.0,1.75,3.0; 3.0; 5.0; 2.0,3.25
+kL3pz7YSQF,,ICLR2026,"Text-to-Image Diffusion Models Cannot Count, and Prompt Refinement Cannot Help",reject,rejected_gt10,datasets and benchmarks,2503.06884,25-09-07,,22,3.142857,4; 6; 4; 4,4.5,4.0; 3.0; 2.0; 4.0,3.25,2.0; 2.0; 2.0; 2.0,2.0,4.0; 3.0; 2.0; 2.0,2.75,4.0; 3.0; 3.0; 4.0,3.5
+t5uLZSRjhF,,ICLR2026,Diffusion LLMs Can Do Faster-Than-AR Inference via Discrete Diffusion Forcing,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2508.09192,25-09-17,,41,6.833333,6; 6; 6; 6,6.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 2.0; 2.0,2.25,4.0; 3.0; 4.0; 3.0,3.5
+JYwGNKfPPp,,ICLR2026,Unveiling Super Experts in Mixture-of-Experts Large Language Models,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2507.23279,25-09-16,,15,2.5,6; 4; 6; 6,5.5,3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 3.0; 3.0,2.75,3.0; 2.0; 3.0; 3.0,2.75,3.0; 4.0; 4.0; 4.0,3.75
+rYBfuHOGy6,,ICLR2026,Inferring Capabilities from Task Performance with Bayesian Triangulation,reject,rejected_gt10,"other topics in machine learning (i.e., none of the above)",2309.11975,25-09-18,,18,3.0,2; 2; 6; 4,3.5,2.0; 3.0; 3.0; 2.0,2.5,3.0; 2.0; 3.0; 3.0,2.75,2.0; 2.0; 2.0; 2.0,2.0,2.0; 3.0; 4.0; 2.0,2.75
+Ovu02vITZN,,ICLR2026,"Signed in Ink, Hidden in Noise: Watermarking Diffusion Large Language Models",reject,rejected_gt10,"alignment, fairness, safety, privacy, and societal considerations",,25-09-17,,40,6.666667,4; 6; 2; 2,3.5,3.0; 3.0; 1.0; 3.0,2.5,2.0; 3.0; 2.0; 2.0,2.25,3.0; 3.0; 2.0; 2.0,2.5,3.0; 5.0; 4.0; 4.0,4.0
+VmojW15eRc,,ICLR2026,Expected Attention: KV Cache Compression by Estimating Attention From Future Queries Distribution,reject,rejected_gt10,"foundation or frontier models, including LLMs",2510.00636,25-09-19,25-10-01,11,1.833333,6; 4; 4; 6,5.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 3.0; 3.0,2.75,3.0; 3.0; 3.0; 3.0,3.0,3.0; 4.0; 3.0; 4.0,3.5
+C3F0G9nXhl,,ICLR2026,MobileRL: Online Agentic Reinforcement Learning for Mobile GUI Agents,accept (poster),accepted_gt10,"applications to robotics, autonomy, planning",2509.18119,25-09-01,25-09-10,11,1.571429,4; 8; 4; 2,4.5,3.0; 4.0; 3.0; 2.0,3.0,3.0; 4.0; 2.0; 3.0,3.0,3.0; 3.0; 2.0; 2.0,2.5,4.0; 5.0; 4.0; 3.0,4.0
+Tb9qAxT3xv,,ICLR2026,Test-Time Training Done Right,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2505.23884,25-09-18,25-05-29,188,31.333333,4; 6; 8; 6; 4,5.6,2.0; 2.0; 4.0; 2.0; 3.0,2.6,3.0; 4.0; 3.0; 3.0; 3.0,3.2,2.0; 3.0; 3.0; 3.0; 2.0,2.6,3.0; 3.0; 3.0; 3.0; 4.0,3.2
+3c6bnSJwDg,,ICLR2026,DexMachina: Functional Retargeting for Bimanual Dexterous Manipulation,reject,rejected_gt10,"applications to robotics, autonomy, planning",2505.24853,25-09-15,25-05-30,21,3.5,6; 6; 6; 4,5.5,3.0; 4.0; 3.0; 3.0,3.25,3.0; 2.0; 3.0; 2.0,2.5,3.0; 2.0; 3.0; 2.0,2.5,4.0; 3.0; 4.0; 4.0,3.75
+12jdbVQ7t0,,ICLR2026,Lattice: Learning to Efficiently Compress the Memory,reject,rejected_gt10,"foundation or frontier models, including LLMs",2504.05646,25-09-17,,11,1.833333,8; 4; 4; 4; 6,5.2,3.0; 2.0; 3.0; 2.0; 3.0,2.6,3.0; 3.0; 3.0; 2.0; 3.0,2.8,3.0; 2.0; 2.0; 3.0; 4.0,2.8,2.0; 3.0; 4.0; 3.0; 2.0,2.8
+cRmIcXyAG1,,ICLR2026,Analysis of Variational Autoencoders,desk reject,rejected_gt10,interpretability and explainable AI,,25-09-20,,625,104.166667,,,,,,,,,,
+SnEywLKodN,,ICLR2026,VeriGuard: Enhancing LLM Agent Safety via Verified Code Generation,reject,rejected_gt10,"alignment, fairness, safety, privacy, and societal considerations",2510.05156,25-09-19,25-10-03,11,1.833333,4; 4; 2; 4,3.5,1.0; 1.0; 2.0; 3.0,1.75,3.0; 2.0; 2.0; 2.0,2.25,3.0; 2.0; 2.0; 3.0,2.5,3.0; 5.0; 3.0; 2.0,3.25
+UUE6HEtjhu,,ICLR2026,AutoBio: A Simulation and Benchmark for Robotic Automation in Digital Biology Laboratory,accept (poster),accepted_gt10,datasets and benchmarks,2505.14030,25-09-18,,11,1.833333,8; 8; 6; 6,7.0,3.0; 4.0; 3.0; 3.0,3.25,4.0; 4.0; 3.0; 3.0,3.5,3.0; 4.0; 4.0; 3.0,3.5,3.0; 4.0; 4.0; 3.0,3.5
+0wSlFpMsGb,,ICLR2026,Common Corpus: The Largest Collection of Ethical Data for LLM Pre-Training,accept (oral),accepted_gt10,datasets and benchmarks,2506.01732,25-09-20,,14,2.333333,8; 8; 6; 6,7.0,2.0; 3.0; 3.0; 3.0,2.75,3.0; 3.0; 3.0; 3.0,3.0,3.0; 4.0; 3.0; 3.0,3.25,5.0; 3.0; 4.0; 4.0,4.0
+oQaRElUdmh,,ICLR2026,VMoBA: Mixture-of-Block Attention for Video Diffusion Models,accept (poster),accepted_gt10,generative models,2506.23858,25-09-18,25-06-30,24,4.0,4; 8; 4; 6,5.5,3.0; 4.0; 3.0; 3.0,3.25,3.0; 3.0; 2.0; 3.0,2.75,3.0; 3.0; 2.0; 3.0,2.75,4.0; 3.0; 5.0; 4.0,4.0
+SiqK9UzqNT,,ICLR2026,Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Models,reject,rejected_gt10,"applications to computer vision, audio, language, and other modalities",2502.05505,25-09-18,25-02-08,13,2.166667,2; 6; 6; 2,4.0,3.0; 4.0; 4.0; 2.0,3.25,3.0; 3.0; 3.0; 2.0,2.75,2.0; 4.0; 3.0; 2.0,2.75,4.0; 4.0; 3.0; 5.0,4.0
+VJZ477R89F,,ICLR2026,DiffusionNFT: Online Diffusion Reinforcement with Forward Process,accept (oral),accepted_gt10,generative models,2509.16117,25-09-17,25-09-19,45,7.5,8; 6; 8,7.333333,2.0; 3.0; 2.0,2.3333,4.0; 3.0; 3.0,3.3333,3.0; 3.0; 3.0,3.0,4.0; 4.0; 3.0,3.6667
+vI56m4Iu4e,,ICLR2026,MemGen: Weaving Generative Latent Memory for Self-Evolving Agents,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2509.24704,25-09-09,,31,4.428571,8; 4; 8; 8,7.0,3.0; 3.0; 3.0; 2.0,2.75,3.0; 3.0; 4.0; 3.0,3.25,3.0; 3.0; 3.0; 4.0,3.25,5.0; 4.0; 4.0; 4.0,4.25
+H1KDMNOKQn,,ICLR2026,HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model,accept (poster),accepted_gt10,"applications to robotics, autonomy, planning",2503.10631,25-09-18,25-03-13,148,24.666667,4; 6; 6; 2,4.5,3.0; 4.0; 3.0; 3.0,3.25,3.0; 4.0; 3.0; 2.0,3.0,2.0; 4.0; 3.0; 2.0,2.75,3.0; 3.0; 4.0; 5.0,3.75
+XtLQHlNLxy,,ICLR2026,"Wide-In, Narrow-Out: Revokable Decoding for Efficient and Effective DLLMs",accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2507.18578,25-09-05,,22,3.142857,6; 6; 6; 2,5.0,3.0; 2.0; 3.0; 3.0,2.75,2.0; 3.0; 3.0; 3.0,2.75,3.0; 3.0; 3.0; 2.0,2.75,3.0; 3.0; 4.0; 3.0,3.25
+Nbbzu9SDzM,,ICLR2026,Recasting Transformer Layers as Energy Models,desk reject,rejected_gt10,"foundation or frontier models, including LLMs",,25-09-19,,126,21.0,4; 6; 6; 6,5.5,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 3.0,3.0,4.0; 3.0; 3.0; 3.0,3.25,4.0; 3.0; 2.0; 4.0,3.25
+q95Hql3QBk,,ICLR2026,Invariant and equivariant architectures via learned polarization,reject,rejected_gt10,learning on graphs and other geometries & topologies,,25-09-20,,160,26.666667,2; 2; 2; 2,2.0,2.0; 2.0; 4.0; 3.0,2.75,3.0; 1.0; 4.0; 2.0,2.5,1.0; 2.0; 1.0; 1.0,1.25,2.0; 4.0; 4.0; 4.0,3.5
+Vsoor99Ts6,,ICLR2026,Context is All You Need,reject,rejected_gt10,"other topics in machine learning (i.e., none of the above)",,25-09-19,,772,128.666667,2; 2; 2; 6,3.0,1.0; 2.0; 3.0; 2.0,2.0,1.0; 2.0; 2.0; 3.0,2.0,2.0; 2.0; 2.0; 3.0,2.25,4.0; 4.0; 4.0; 1.0,3.25
+osnAy1yTHu,,ICLR2026,OneReward: Unified Mask-Guided Image Generation via Multi-Task Human Preference Learning,reject,rejected_gt10,generative models,2508.21066,25-09-03,,12,1.714286,4; 4; 6; 4,4.5,3.0; 2.0; 3.0; 3.0,2.75,3.0; 1.0; 3.0; 2.0,2.25,3.0; 3.0; 3.0; 3.0,3.0,3.0; 4.0; 4.0; 3.0,3.5
+mlzh3jX6gW,,ICLR2026,Navigate the Unknown: Enhancing LLM Reasoning with Intrinsic Motivation Guided Exploration,reject,rejected_gt10,"applications to computer vision, audio, language, and other modalities",2505.17621,25-09-19,,20,3.333333,4; 6; 4; 8,5.5,2.0; 3.0; 3.0; 2.0,2.5,2.0; 2.0; 3.0; 3.0,2.5,2.0; 2.0; 2.0; 2.0,2.0,4.0; 4.0; 4.0; 3.0,3.75
+5Z1eMhCeTb,,ICLR2026,STITCH: Simultaneous Thinking and Talking with Chunked Reasoning for Spoken Language Models,accept (poster),accepted_gt10,"applications to computer vision, audio, language, and other modalities",2507.15375,25-09-15,25-07-21,12,2.0,4; 6; 4; 6,5.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 2.0; 3.0,2.75,3.0; 3.0; 3.0; 5.0,3.5
+oWFtI0cNsE,,ICLR2026,Verl-Tool: Towards Holistic Agentic Reinforcement Learning with Tool Use,reject,rejected_gt10,reinforcement learning,2509.01055,25-09-18,25-09-01,51,8.5,4; 6; 4; 4,4.5,3.0; 4.0; 3.0; 4.0,3.5,1.0; 4.0; 3.0; 3.0,2.75,4.0; 4.0; 2.0; 3.0,3.25,5.0; 4.0; 2.0; 4.0,3.75
+5jJrmvPO0z,,ICLR2026,Unified Single Transformer for Multimodal Video Understanding and Generation,reject,rejected_gt10,"foundation or frontier models, including LLMs",2506.02975,25-09-19,25-06-03,11,1.833333,4; 2; 4; 4,3.5,2.0; 2.0; 3.0; 3.0,2.5,3.0; 2.0; 3.0; 2.0,2.5,3.0; 1.0; 2.0; 2.0,2.0,4.0; 3.0; 4.0; 4.0,3.75
+iqAFhWistW,,ICLR2026,"Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?",accept (poster),accepted_gt10,datasets and benchmarks,2509.03516,25-09-15,,11,1.833333,8; 4; 6; 6,6.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 2.0; 3.0,2.75,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 4.0,3.25
+B92Lzl1b3j,,ICLR2026,GSFixer: Improving 3D Gaussian Splatting with Reference-Guided Video Diffusion Priors,reject,rejected_gt10,"applications to computer vision, audio, language, and other modalities",2508.09667,25-09-13,,12,2.0,4; 4; 6; 6,5.0,2.0; 3.0; 2.0; 4.0,2.75,2.0; 3.0; 3.0; 3.0,2.75,1.0; 2.0; 3.0; 2.0,2.0,5.0; 3.0; 5.0; 5.0,4.5
+iPAy5VpGQa,,ICLR2026,HiMAE: Hierarchical Masked Autoencoders Discover Resolution-Specific Structure in Wearable Time Series,accept (poster),accepted_gt10,"applications to physical sciences (physics, chemistry, biology, etc.)",2510.25785,25-09-19,25-10-28,19,3.166667,2; 4; 6,4.0,1.0; 3.0; 2.0,2.0,2.0; 3.0; 3.0,2.6667,3.0; 3.0; 3.0,3.0,3.0; 5.0; 4.0,4.0
+mmkbgNlrJB,,ICLR2026,ZeroSearch: Incentivize the Search Capability of LLMs without Searching,desk reject,rejected_gt10,reinforcement learning,2505.04588,25-09-14,25-05-07,125,20.833333,6; 4; 8; 2,5.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 3.0; 1.0,2.25,3.0; 2.0; 3.0; 1.0,2.25,4.0; 4.0; 3.0; 5.0,4.0
+OvgcxUZyZV,,ICLR2026,BRIDGE: A Risk-Aware Framework for Evaluating Behavioral Fidelity in LLM Agents,reject,rejected_gt10,interpretability and explainable AI,,25-09-16,,196,32.666667,6; 4; 2; 4,4.0,3.0; 3.0; 2.0; 2.0,2.5,2.0; 2.0; 2.0; 3.0,2.25,3.0; 2.0; 2.0; 2.0,2.25,2.0; 3.0; 3.0; 4.0,3.0
+zV5FeNiWDO,,ICLR2026,Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2509.19244,25-09-18,25-09-23,11,1.833333,4; 8; 6; 6,6.0,3.0; 4.0; 4.0; 3.0,3.5,2.0; 4.0; 4.0; 3.0,3.25,2.0; 3.0; 3.0; 3.0,2.75,4.0; 3.0; 4.0; 4.0,3.75
+qe060gmfm7,,ICLR2026,On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning,accept (poster),accepted_gt10,reinforcement learning,2505.17508,25-09-19,25-05-23,13,2.166667,4; 4; 6,4.666667,2.0; 2.0; 3.0,2.3333,3.0; 3.0; 4.0,3.3333,3.0; 3.0; 3.0,3.0,4.0; 3.0; 3.0,3.3333
+k3Cyx3Uets,,ICLR2026,From Language to Locomotion: Retargeting-free Humanoid Control via Motion Latent Guidance,accept (poster),accepted_gt10,"applications to robotics, autonomy, planning",2510.14952,25-09-01,25-10-16,15,2.142857,6; 8; 2; 4,5.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 2.0; 2.0,2.5,3.0; 3.0; 2.0; 3.0,2.75,4.0; 3.0; 4.0; 4.0,3.75
+CFF6zXErgS,,ICLR2026,GTPO AND GRPO-S: TOKEN AND SEQUENCE-LEVEL REWARD SHAPING WITH POLICY ENTROPY,reject,rejected_gt10,reinforcement learning,2508.04349,25-09-10,25-08-06,27,3.857143,2; 2; 2; 4,2.5,2.0; 2.0; 2.0; 3.0,2.25,2.0; 2.0; 2.0; 3.0,2.25,2.0; 2.0; 2.0; 2.0,2.0,3.0; 4.0; 4.0; 4.0,3.75
+GhqnOEXQh3,,ICLR2026,PosterCraft: Rethinking High-Quality Aesthetic Poster Generation in a Unified Framework,accept (poster),accepted_gt10,generative models,2506.10741,25-09-04,,17,2.428571,4; 4; 8; 4,5.0,3.0; 3.0; 4.0; 3.0,3.25,3.0; 2.0; 4.0; 2.0,2.75,2.0; 3.0; 3.0; 2.0,2.5,4.0; 3.0; 3.0; 5.0,3.75
+y5CaJb17Fn,,ICLR2026,villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models,accept (poster),accepted_gt10,"applications to robotics, autonomy, planning",2507.23682,25-09-18,,34,5.666667,6; 4; 8; 6,6.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 3.0; 2.0,2.5,3.0; 4.0; 4.0; 4.0,3.75
+gHRoX4vXm3,,ICLR2026,MMSI-Bench: A Benchmark for Multi-Image Spatial Intelligence,accept (poster),accepted_gt10,datasets and benchmarks,2505.23764,25-09-09,,79,11.285714,6; 8; 4; 8,6.5,2.0; 4.0; 3.0; 4.0,3.25,3.0; 3.0; 3.0; 4.0,3.25,3.0; 3.0; 3.0; 3.0,3.0,4.0; 4.0; 3.0; 4.0,3.75
+Mf5AleTUVK,,ICLR2026,In-the-Flow Agentic System Optimization for Effective Planning and Tool Use,accept (oral),accepted_gt10,"applications to computer vision, audio, language, and other modalities",2510.05592,25-09-19,,30,5.0,8; 8; 6,7.333333,4.0; 3.0; 1.0,2.6667,3.0; 3.0; 3.0,3.0,4.0; 3.0; 2.0,3.0,3.0; 3.0; 2.0,2.6667
+UtzdSeit84,,ICLR2026,MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision,reject,rejected_gt10,"foundation or frontier models, including LLMs",2505.13427,25-09-19,,17,2.833333,6; 4; 4; 2,4.0,3.0; 3.0; 2.0; 3.0,2.75,2.0; 3.0; 3.0; 2.0,2.5,2.0; 2.0; 2.0; 1.0,1.75,4.0; 2.0; 5.0; 4.0,3.75
+dyJ0GWpjJB,,ICLR2026,LightMem: Lightweight and Efficient Memory-Augmented Generation,accept (poster),accepted_gt10,"foundation or frontier models, including LLMs",2510.18866,25-09-20,25-10-21,38,6.333333,4; 6; 6; 6; 8,6.0,2.0; 3.0; 3.0; 3.0; 3.0,2.8,3.0; 3.0; 3.0; 3.0; 3.0,3.0,3.0; 3.0; 3.0; 3.0; 3.0,3.0,3.0; 2.0; 3.0; 1.0; 3.0,2.4