arxiv_id string | pwc_url string | status int64 | found bool | pwc_id string | title string | url_abs string | repositories list | project_pages list | hf_models list | hf_datasets list | hf_spaces list |
|---|---|---|---|---|---|---|---|---|---|---|---|
2510.26955 | https://paperswithcode.co/api/v1/papers/arxiv/2510.26955?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.01374 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01374?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.16171 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16171?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.10465 | https://paperswithcode.co/api/v1/papers/arxiv/2505.10465?include_resources=true | 200 | true | 48775 | Superposition Yields Robust Neural Scaling | https://arxiv.org/abs/2505.10465v2 | [
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"owner": "liuyz0",
"name": "superpositionscaling",
"stars": 32,
"is_official": true,
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] | [] | [] | [] | [] |
2505.14631 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14631?include_resources=true | 200 | true | 49204 | Think Only When You Need with Large Hybrid-Reasoning Models | https://arxiv.org/abs/2505.14631v2 | [] | [] | [] | [] | [] |
2511.00530 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00530?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.00116 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00116?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2508.12815 | https://paperswithcode.co/api/v1/papers/arxiv/2508.12815?include_resources=true | 200 | true | 85851 | Learning to Steer: Input-dependent Steering for Multimodal LLMs | https://arxiv.org/abs/2508.12815 | [] | [] | [] | [] | [] |
2506.07977 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07977?include_resources=true | 200 | true | 50803 | OneIG-Bench: Omni-dimensional Nuanced Evaluation for Image Generation | https://arxiv.org/abs/2506.07977v2 | [
{
"url": "https://github.com/oneig-bench/oneig-benchmark",
"owner": "OneIG-Bench",
"name": "OneIG-Benchmark",
"stars": 94,
"is_official": true,
"source": "links_json"
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] | [
{
"url": "https://oneig-bench.github.io/",
"is_official": true
}
] | [] | [] | [] |
2502.04262 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04262?include_resources=true | 200 | true | 86383 | Efficient Randomized Experiments Using Foundation Models | https://arxiv.org/abs/2502.04262 | [] | [] | [] | [] | [] |
2505.23623 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23623?include_resources=true | 200 | true | 86953 | Characterizing the Expressivity of Transformer Language Models | https://arxiv.org/abs/2505.23623 | [] | [] | [] | [] | [] |
2505.16270 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16270?include_resources=true | 200 | true | 49388 | Transformer Copilot: Learning from The Mistake Log in LLM Fine-tuning | https://arxiv.org/abs/2505.16270 | [
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"url": "https://github.com/jiaruzouu/transformercopilot",
"owner": "jiaruzouu",
"name": "TransformerCopilot",
"stars": 11,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2511.08178 | https://paperswithcode.co/api/v1/papers/arxiv/2511.08178?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.11151 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11151?include_resources=true | 200 | true | 48839 | STEP: A Unified Spiking Transformer Evaluation Platform for Fair and Reproducible Benchmarking | https://arxiv.org/abs/2505.11151 | [
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"url": "https://github.com/fancyssc/step",
"owner": "Fancyssc",
"name": "STEP",
"stars": 14,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.15231 | https://paperswithcode.co/api/v1/papers/arxiv/2505.15231?include_resources=true | 200 | true | 86958 | Finding separatrices of dynamical flows with Deep Koopman Eigenfunctions | https://arxiv.org/abs/2505.15231 | [] | [] | [] | [] | [] |
2506.13030 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13030?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2405.16276 | https://paperswithcode.co/api/v1/papers/arxiv/2405.16276?include_resources=true | 200 | true | 85801 | Mechanism Design for LLM Fine-tuning with Multiple Reward Models | https://arxiv.org/abs/2405.16276 | [] | [] | [] | [] | [] |
2512.03058 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03058?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.21770 | https://paperswithcode.co/api/v1/papers/arxiv/2503.21770?include_resources=true | 200 | true | 85991 | Visual Jenga: Discovering Object Dependencies via Counterfactual Inpainting | https://arxiv.org/abs/2503.21770 | [] | [] | [] | [] | [] |
2505.06535 | https://paperswithcode.co/api/v1/papers/arxiv/2505.06535?include_resources=true | 200 | true | 87103 | Online Feedback Efficient Active Target Discovery in Partially Observable Environments | https://arxiv.org/abs/2505.06535 | [] | [] | [] | [] | [] |
2408.15332 | https://paperswithcode.co/api/v1/papers/arxiv/2408.15332?include_resources=true | 200 | true | 76506 | What makes math problems hard for reinforcement learning: a case study | https://arxiv.org/abs/2408.15332 | [] | [] | [] | [] | [] |
2506.05271 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05271?include_resources=true | 200 | true | 85783 | Tight analyses of first-order methods with error feedback | https://arxiv.org/abs/2506.05271 | [] | [] | [] | [] | [] |
2509.16875 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16875?include_resources=true | 200 | true | 87290 | Towards Interpretable and Efficient Attention: Compressing All by Contracting a Few | https://arxiv.org/abs/2509.16875 | [] | [] | [] | [] | [] |
2510.20406 | https://paperswithcode.co/api/v1/papers/arxiv/2510.20406?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.16852 | https://paperswithcode.co/api/v1/papers/arxiv/2502.16852?include_resources=true | 200 | true | 44879 | Improving LLM General Preference Alignment via Optimistic Online Mirror Descent | https://arxiv.org/abs/2502.16852 | [] | [] | [] | [] | [] |
2506.04171 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04171?include_resources=true | 200 | true | 85794 | Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints | https://arxiv.org/abs/2506.04171 | [] | [] | [] | [] | [] |
2506.02408 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02408?include_resources=true | 200 | true | 50449 | Revisiting End-to-End Learning with Slide-level Supervision in Computational Pathology | https://arxiv.org/abs/2506.02408 | [
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"owner": "DearCaat",
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"url": "https://github.com/dearcaat/rrt-mil",
"owner": "dearcaat",
"name": "rrt-mil",
"stars": 132,
"is_... | [] | [] | [] | [] |
2505.13898 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13898?include_resources=true | 200 | true | 49105 | Do Language Models Use Their Depth Efficiently? | https://arxiv.org/abs/2505.13898 | [
{
"url": "https://github.com/robertcsordas/llm_effective_depth",
"owner": "robertcsordas",
"name": "llm_effective_depth",
"stars": 24,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2508.14881 | https://paperswithcode.co/api/v1/papers/arxiv/2508.14881?include_resources=true | 200 | true | 86060 | Compute-Optimal Scaling for Value-Based Deep RL | https://arxiv.org/abs/2508.14881 | [] | [] | [] | [] | [] |
2511.13993 | https://paperswithcode.co/api/v1/papers/arxiv/2511.13993?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.12944 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12944?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.12140 | https://paperswithcode.co/api/v1/papers/arxiv/2510.12140?include_resources=true | 200 | true | 86430 | Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration | https://arxiv.org/abs/2510.12140 | [] | [] | [] | [] | [] |
2505.23061 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23061?include_resources=true | 200 | true | 50078 | DINGO: Constrained Inference for Diffusion LLMs | https://arxiv.org/abs/2505.23061 | [] | [] | [] | [] | [] |
2505.13413 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13413?include_resources=true | 200 | true | 49059 | Joint Velocity-Growth Flow Matching for Single-Cell Dynamics Modeling | https://arxiv.org/abs/2505.13413 | [] | [] | [] | [] | [] |
2505.20809 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20809?include_resources=true | 200 | true | 49906 | Improved Representation Steering for Language Models | https://arxiv.org/abs/2505.20809 | [
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"owner": "stanfordnlp",
"name": "axbench",
"stars": 158,
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] | [] | [] | [] | [] |
2506.06571 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06571?include_resources=true | 200 | true | 85744 | Graph Persistence goes Spectral | https://arxiv.org/abs/2506.06571 | [] | [] | [] | [] | [] |
2506.06318 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06318?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.18740 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18740?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.05682 | https://paperswithcode.co/api/v1/papers/arxiv/2511.05682?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.00022 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00022?include_resources=true | 200 | true | 50286 | Scaling Physical Reasoning with the PHYSICS Dataset | https://arxiv.org/abs/2506.00022v2 | [] | [] | [] | [] | [] |
2412.08843 | https://paperswithcode.co/api/v1/papers/arxiv/2412.08843?include_resources=true | 200 | true | 87246 | Precise Asymptotics and Refined Regret of Variance-Aware UCB | https://arxiv.org/abs/2412.08843 | [] | [] | [] | [] | [] |
2507.10741 | https://paperswithcode.co/api/v1/papers/arxiv/2507.10741?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.12116 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12116?include_resources=true | 200 | true | 48926 | A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings | https://arxiv.org/abs/2505.12116 | [
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"name": "tigrinya-abusive-language-detection",
"stars": 8,
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] | [] | [] | [] | [] |
2506.05454 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05454?include_resources=true | 200 | true | 86593 | Zeroth-Order Optimization Finds Flat Minima | https://arxiv.org/abs/2506.05454 | [] | [] | [] | [] | [] |
2412.01463 | https://paperswithcode.co/api/v1/papers/arxiv/2412.01463?include_resources=true | 200 | true | 87035 | Learning Differential Pyramid Representation for Tone Mapping | https://arxiv.org/abs/2412.01463 | [] | [] | [] | [] | [] |
2504.11453 | https://paperswithcode.co/api/v1/papers/arxiv/2504.11453?include_resources=true | 200 | true | 85835 | A Clean Slate for Offline Reinforcement Learning | https://arxiv.org/abs/2504.11453 | [
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"owner": "emptyjackson",
"name": "unifloral",
"stars": 217,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2401.08348 | https://paperswithcode.co/api/v1/papers/arxiv/2401.08348?include_resources=true | 200 | true | 25856 | Estimating Model Performance Under Covariate Shift Without Labels | https://arxiv.org/abs/2401.08348v3 | [] | [] | [] | [] | [] |
2511.03256 | https://paperswithcode.co/api/v1/papers/arxiv/2511.03256?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2506.01977 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01977?include_resources=true | 200 | true | 87147 | Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN | https://arxiv.org/abs/2506.01977 | [] | [] | [] | [] | [] |
2502.14560 | https://paperswithcode.co/api/v1/papers/arxiv/2502.14560?include_resources=true | 200 | true | 44662 | Less is More: Improving LLM Alignment via Preference Data Selection | https://arxiv.org/abs/2502.14560 | [
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2505.14552 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14552?include_resources=true | 200 | true | 49192 | KORGym: A Dynamic Game Platform for LLM Reasoning Evaluation | https://arxiv.org/abs/2505.14552v2 | [
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"name": "korgym",
"stars": 52,
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] | [] | [] | [] | [] |
2502.15798 | https://paperswithcode.co/api/v1/papers/arxiv/2502.15798?include_resources=true | 200 | true | 44784 | MaxSup: Overcoming Representation Collapse in Label Smoothing | https://arxiv.org/abs/2502.15798 | [
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"owner": "ZhouYuxuanYX",
"name": "Maximum-Suppression-Regularization",
"stars": 15,
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2511.18890 | https://paperswithcode.co/api/v1/papers/arxiv/2511.18890?include_resources=true | 200 | true | 54423 | Nemotron-Flash: Towards Latency-Optimal Hybrid Small Language Models | https://arxiv.org/abs/2511.18890 | [] | [] | [] | [] | [] |
2509.20824 | https://paperswithcode.co/api/v1/papers/arxiv/2509.20824?include_resources=true | 200 | true | 86748 | ARMesh: Autoregressive Mesh Generation via Next-Level-of-Detail Prediction | https://arxiv.org/abs/2509.20824 | [] | [] | [] | [] | [] |
2506.00070 | https://paperswithcode.co/api/v1/papers/arxiv/2506.00070?include_resources=true | 200 | true | 50288 | Robot-R1: Reinforcement Learning for Enhanced Embodied Reasoning in Robotics | https://arxiv.org/abs/2506.00070 | [] | [] | [] | [] | [] |
2505.21939 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21939?include_resources=true | 200 | true | 87220 | Improved Approximation Algorithms for Chromatic and Pseudometric-Weighted Correlation Clustering | https://arxiv.org/abs/2505.21939 | [] | [] | [] | [] | [] |
2512.24323 | https://paperswithcode.co/api/v1/papers/arxiv/2512.24323?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.21089 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21089?include_resources=true | 200 | true | 72652 | DisasterM3: A Remote Sensing Vision-Language Dataset for Disaster Damage
Assessment and Response | https://arxiv.org/abs/2505.21089 | [
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"owner": "Junjue-Wang",
"name": "DisasterM3",
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"url": "https://github.com/Junjue-Wang/DisasterM3",
"is_official": true
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2406.05014 | https://paperswithcode.co/api/v1/papers/arxiv/2406.05014?include_resources=true | 200 | true | 87002 | Root Cause Analysis of Outliers with Missing Structural Knowledge | https://arxiv.org/abs/2406.05014 | [] | [] | [] | [] | [] |
2510.19796 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19796?include_resources=true | 200 | true | 66020 | Blackbox Model Provenance via Palimpsestic Membership Inference | https://arxiv.org/abs/2510.19796 | [] | [] | [] | [] | [] |
2505.24022 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24022?include_resources=true | 200 | true | 87249 | The Rich and the Simple: On the Implicit Bias of Adam and SGD | https://arxiv.org/abs/2505.24022 | [] | [] | [] | [] | [] |
2506.21996 | https://paperswithcode.co/api/v1/papers/arxiv/2506.21996?include_resources=true | 200 | true | 85945 | AlphaBeta is not as good as you think: a new probabilistic model to better analyze deterministic game-solving algorithms | https://arxiv.org/abs/2506.21996 | [] | [] | [] | [] | [] |
2505.16927 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16927?include_resources=true | 200 | true | 86010 | Latent Principle Discovery for Language Model Self-Improvement | https://arxiv.org/abs/2505.16927 | [] | [] | [] | [] | [] |
2510.19710 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19710?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.16826 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16826?include_resources=true | 200 | true | 49444 | KTAE: A Model-Free Algorithm to Key-Tokens Advantage Estimation in Mathematical Reasoning | https://arxiv.org/abs/2505.16826 | [
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"name": "ktae",
"stars": 9,
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] | [] | [] | [] | [] |
2505.22422 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22422?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.11843 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11843?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.24290 | https://paperswithcode.co/api/v1/papers/arxiv/2503.24290?include_resources=true | 200 | true | 47064 | Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model | https://arxiv.org/abs/2503.24290 | [
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"url": "https://huggingface.co/Open-Reasoner-Zero",
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2501.19122 | https://paperswithcode.co/api/v1/papers/arxiv/2501.19122?include_resources=true | 200 | true | 86306 | FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling | https://arxiv.org/abs/2501.19122 | [
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2408.01798 | https://paperswithcode.co/api/v1/papers/arxiv/2408.01798?include_resources=true | 200 | true | 87323 | Differentially Private Gomory-Hu Trees | https://arxiv.org/abs/2408.01798 | [] | [] | [] | [] | [] |
2503.01422 | https://paperswithcode.co/api/v1/papers/arxiv/2503.01422?include_resources=true | 200 | true | 74344 | Sampling-Efficient Test-Time Scaling: Self-Estimating the Best-of-N
Sampling in Early Decoding | https://arxiv.org/abs/2503.01422 | [] | [] | [] | [] | [] |
2502.16076 | https://paperswithcode.co/api/v1/papers/arxiv/2502.16076?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.07696 | https://paperswithcode.co/api/v1/papers/arxiv/2511.07696?include_resources=true | 200 | true | 65205 | FlowFeat: Pixel-Dense Embedding of Motion Profiles | https://arxiv.org/abs/2511.07696 | [] | [] | [] | [] | [] |
2508.06635 | https://paperswithcode.co/api/v1/papers/arxiv/2508.06635?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.11193 | https://paperswithcode.co/api/v1/papers/arxiv/2512.11193?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.13143 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13143?include_resources=true | 200 | true | 87134 | Auditing Meta-Cognitive Hallucinations in Reasoning Large Language Models | https://arxiv.org/abs/2505.13143 | [] | [] | [] | [] | [] |
2510.16376 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16376?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2503.07649 | https://paperswithcode.co/api/v1/papers/arxiv/2503.07649?include_resources=true | 200 | true | 74252 | TS-RAG: Retrieval-Augmented Generation based Time Series Foundation Models are Stronger Zero-Shot Forecaster | https://arxiv.org/abs/2503.07649 | [
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] | [] | [] | [] | [] |
2505.20444 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20444?include_resources=true | 200 | true | 49882 | HoPE: Hybrid of Position Embedding for Length Generalization in Vision-Language Models | https://arxiv.org/abs/2505.20444 | [
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2412.19634 | https://paperswithcode.co/api/v1/papers/arxiv/2412.19634?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2405.15167 | https://paperswithcode.co/api/v1/papers/arxiv/2405.15167?include_resources=true | 200 | true | 86510 | ProDAG: Projected Variational Inference for Directed Acyclic Graphs | https://arxiv.org/abs/2405.15167 | [] | [] | [] | [] | [] |
2506.09024 | https://paperswithcode.co/api/v1/papers/arxiv/2506.09024?include_resources=true | 200 | true | 86579 | DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging | https://arxiv.org/abs/2506.09024 | [] | [] | [] | [] | [] |
2508.02110 | https://paperswithcode.co/api/v1/papers/arxiv/2508.02110?include_resources=true | 200 | true | 87455 | Attractive Metadata Attack: Inducing LLM Agents to Invoke Malicious Tools | https://arxiv.org/abs/2508.02110 | [] | [] | [] | [] | [] |
2505.22049 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22049?include_resources=true | 200 | true | 87331 | Differentiable Generalized Sliced Wasserstein Plans | https://arxiv.org/abs/2505.22049 | [] | [] | [] | [] | [] |
2505.13544 | https://paperswithcode.co/api/v1/papers/arxiv/2505.13544?include_resources=true | 200 | true | 49081 | Multi-head Temporal Latent Attention | https://arxiv.org/abs/2505.13544v2 | [
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2505.19013 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19013?include_resources=true | 200 | true | 86998 | Faithful Group Shapley Value | https://arxiv.org/abs/2505.19013 | [] | [] | [] | [] | [] |
2505.16836 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16836?include_resources=true | 200 | true | 49446 | Fact-R1: Towards Explainable Video Misinformation Detection with Deep Reasoning | https://arxiv.org/abs/2505.16836 | [
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2505.23871 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23871?include_resources=true | 200 | true | 72547 | ADG: Ambient Diffusion-Guided Dataset Recovery for Corruption-Robust Offline Reinforcement Learning | https://arxiv.org/abs/2505.23871 | [] | [] | [] | [] | [] |
2408.10858 | https://paperswithcode.co/api/v1/papers/arxiv/2408.10858?include_resources=true | 200 | true | 86951 | Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning | https://arxiv.org/abs/2408.10858 | [] | [] | [] | [] | [] |
2506.13691 | https://paperswithcode.co/api/v1/papers/arxiv/2506.13691?include_resources=true | 200 | true | 51163 | UltraVideo: High-Quality UHD Video Dataset with Comprehensive Captions | https://arxiv.org/abs/2506.13691 | [
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2502.05795 | https://paperswithcode.co/api/v1/papers/arxiv/2502.05795?include_resources=true | 200 | true | 43887 | The Curse of Depth in Large Language Models | https://arxiv.org/abs/2502.05795 | [
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"name": "LayerNorm-Scaling",
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2505.02391 | https://paperswithcode.co/api/v1/papers/arxiv/2505.02391?include_resources=true | 200 | true | 48393 | Optimizing Chain-of-Thought Reasoners via Gradient Variance Minimization in Rejection Sampling and RL | https://arxiv.org/abs/2505.02391 | [
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2510.04951 | https://paperswithcode.co/api/v1/papers/arxiv/2510.04951?include_resources=true | 200 | true | 86941 | Feasibility-Aware Decision-Focused Learning for Predicting Parameters in the Constraints | https://arxiv.org/abs/2510.04951 | [] | [] | [] | [] | [] |
2510.15362 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15362?include_resources=true | 200 | true | 66261 | RankSEG-RMA: An Efficient Segmentation Algorithm via Reciprocal Moment Approximation | https://arxiv.org/abs/2510.15362 | [] | [] | [] | [] | [] |
2502.08519 | https://paperswithcode.co/api/v1/papers/arxiv/2502.08519?include_resources=true | 200 | true | 86586 | The Complexity of Symmetric Equilibria in Min-Max Optimization and Team Zero-Sum Games | https://arxiv.org/abs/2502.08519 | [] | [] | [] | [] | [] |
2506.19839 | https://paperswithcode.co/api/v1/papers/arxiv/2506.19839?include_resources=true | 200 | true | 51434 | Improving Progressive Generation with Decomposable Flow Matching | https://arxiv.org/abs/2506.19839 | [] | [
{
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2505.16690 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16690?include_resources=true | 200 | true | 85786 | Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator | https://arxiv.org/abs/2505.16690 | [] | [] | [] | [] | [] |
2510.19784 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19784?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.08602 | https://paperswithcode.co/api/v1/papers/arxiv/2510.08602?include_resources=true | 200 | true | 86183 | Human Texts Are Outliers: Detecting LLM-generated Texts via Out-of-distribution Detection | https://arxiv.org/abs/2510.08602 | [] | [] | [] | [] | [] |
2505.16527 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16527?include_resources=true | 200 | true | 87124 | Joint Relational Database Generation via Graph-Conditional Diffusion Models | https://arxiv.org/abs/2505.16527 | [] | [] | [] | [] | [] |
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