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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
2504.07416 | https://paperswithcode.co/api/v1/papers/arxiv/2504.07416?include_resources=true | 200 | true | 47483 | RadZero: Similarity-Based Cross-Attention for Explainable Vision-Language Alignment in Radiology with Zero-Shot Multi-Task Capability | https://arxiv.org/abs/2504.07416 | [
{
"url": "https://github.com/deepnoid-ai/RadZero",
"owner": "deepnoid-ai",
"name": "RadZero",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2509.15566 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15566?include_resources=true | 200 | true | 52880 | BTL-UI: Blink-Think-Link Reasoning Model for GUI Agent | https://arxiv.org/abs/2509.15566 | [
{
"url": "https://github.com/xiaomi-research/btl-ui",
"owner": "xiaomi-research",
"name": "btl-ui",
"stars": 12,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2506.01685 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01685?include_resources=true | 200 | true | 87362 | Geometry Meets Incentives: Sample-Efficient Incentivized Exploration with Linear Contexts | https://arxiv.org/abs/2506.01685 | [] | [] | [] | [] | [] |
2509.16105 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16105?include_resources=true | 200 | true | 68124 | DiEP: Adaptive Mixture-of-Experts Compression through Differentiable Expert Pruning | https://arxiv.org/abs/2509.16105 | [] | [] | [] | [] | [] |
2505.14652 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14652?include_resources=true | 200 | true | 49210 | General-Reasoner: Advancing LLM Reasoning Across All Domains | https://arxiv.org/abs/2505.14652v2 | [
{
"url": "https://github.com/tiger-ai-lab/general-reasoner",
"owner": "TIGER-AI-Lab",
"name": "General-Reasoner",
"stars": 210,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://tiger-ai-lab.github.io/General-Reasoner/",
"is_official": true
}
] | [] | [] | [] |
2510.15363 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15363?include_resources=true | 200 | true | 87230 | Kernel Regression in Structured Non-IID Settings: Theory and Implications for Denoising Score Learning | https://arxiv.org/abs/2510.15363 | [] | [] | [] | [] | [] |
2510.24815 | https://paperswithcode.co/api/v1/papers/arxiv/2510.24815?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.06472 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06472?include_resources=true | 200 | true | 43930 | KARMA: Leveraging Multi-Agent LLMs for Automated Knowledge Graph Enrichment | https://arxiv.org/abs/2502.06472 | [
{
"url": "https://github.com/yuxinglu613/karma",
"owner": "YuxingLu613",
"name": "KARMA",
"stars": 94,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2506.01583 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01583?include_resources=true | 200 | true | 72393 | FreqPolicy: Frequency Autoregressive Visuomotor Policy with Continuous
Tokens | https://arxiv.org/abs/2506.01583 | [
{
"url": "https://github.com/4dvlab/freqpolicy",
"owner": "4DVLab",
"name": "Freqpolicy",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://freq-policy.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.11930 | https://paperswithcode.co/api/v1/papers/arxiv/2505.11930?include_resources=true | 200 | true | 86116 | The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics | https://arxiv.org/abs/2505.11930 | [] | [] | [] | [] | [] |
2506.08010 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08010?include_resources=true | 200 | true | 50818 | Vision Transformers Don't Need Trained Registers | https://arxiv.org/abs/2506.08010 | [
{
"url": "https://github.com/nickjiang2378/test-time-registers",
"owner": "nickjiang2378",
"name": "test-time-registers",
"stars": 153,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://avdravid.github.io/test-time-registers",
"is_official": true
}
] | [] | [] | [] |
2505.20524 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20524?include_resources=true | 200 | true | 72689 | Towards Fully FP8 GEMM LLM Training at Scale | https://arxiv.org/abs/2505.20524 | [] | [] | [] | [] | [] |
2504.12216 | https://paperswithcode.co/api/v1/papers/arxiv/2504.12216?include_resources=true | 200 | true | 47790 | d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning | https://arxiv.org/abs/2504.12216 | [
{
"url": "https://github.com/dllm-reasoning/d1",
"owner": "dllm-reasoning",
"name": "d1",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://dllm-reasoning.github.io/",
"is_official": true
}
] | [] | [] | [] |
2502.02589 | https://paperswithcode.co/api/v1/papers/arxiv/2502.02589?include_resources=true | 200 | true | 43671 | COCONut-PanCap: Joint Panoptic Segmentation and Grounded Captions for Fine-Grained Understanding and Generation | https://arxiv.org/abs/2502.02589 | [
{
"url": "https://github.com/bytedance/coconut_cvpr2024",
"owner": "bytedance",
"name": "coconut_cvpr2024",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [
{
"url": "https://xdeng7.github.io/coconut.github.io/coconut_pancap.html",
"is_official": true
}
] | [] | [] | [] |
2506.05209 | https://paperswithcode.co/api/v1/papers/arxiv/2506.05209?include_resources=true | 200 | true | 50632 | The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text | https://arxiv.org/abs/2506.05209 | [
{
"url": "https://github.com/r-three/common-pile",
"owner": "r-three",
"name": "common-pile",
"stars": 248,
"is_official": true,
"source": "ai_extraction"
}
] | [
{
"url": "https://huggingface.co/common-pile",
"is_official": true
}
] | [] | [] | [] |
2506.08989 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08989?include_resources=true | 200 | true | 50894 | SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning | https://arxiv.org/abs/2506.08989 | [
{
"url": "https://github.com/mastervito/sws",
"owner": "MasterVito",
"name": "SwS",
"stars": 41,
"is_official": true,
"source": "links_json"
}
] | [
{
"url": "https://mastervito.github.io/MasterVito.SwS.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.14036 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14036?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2511.21946 | https://paperswithcode.co/api/v1/papers/arxiv/2511.21946?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.24424 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24424?include_resources=true | 200 | true | 86985 | Advancing Compositional Awareness in CLIP with Efficient Fine-Tuning | https://arxiv.org/abs/2505.24424 | [] | [
{
"url": "https://clic-compositional-clip.github.io/",
"is_official": true
}
] | [] | [] | [] |
2505.24760 | https://paperswithcode.co/api/v1/papers/arxiv/2505.24760?include_resources=true | 200 | true | 50259 | REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards | https://arxiv.org/abs/2505.24760 | [
{
"url": "https://github.com/open-thought/reasoning-gym",
"owner": "open-thought",
"name": "reasoning-gym",
"stars": 1281,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.20755 | https://paperswithcode.co/api/v1/papers/arxiv/2505.20755?include_resources=true | 200 | true | 49900 | Uni-Instruct: One-step Diffusion Model through Unified Diffusion Divergence Instruction | https://arxiv.org/abs/2505.20755 | [] | [] | [] | [] | [] |
2505.22019 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22019?include_resources=true | 200 | true | 49993 | VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning | https://arxiv.org/abs/2505.22019 | [
{
"url": "https://github.com/alibaba-nlp/vrag",
"owner": "Alibaba-NLP",
"name": "VRAG",
"stars": 418,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2509.15399 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15399?include_resources=true | 200 | true | 87433 | Adaptive Algorithms with Sharp Convergence Rates for Stochastic Hierarchical Optimization | https://arxiv.org/abs/2509.15399 | [] | [] | [] | [] | [] |
2505.12366 | https://paperswithcode.co/api/v1/papers/arxiv/2505.12366?include_resources=true | 200 | true | 48955 | DisCO: Reinforcing Large Reasoning Models with Discriminative Constrained Optimization | https://arxiv.org/abs/2505.12366 | [
{
"url": "https://github.com/optimization-ai/disco",
"owner": "optimization-ai",
"name": "disco",
"stars": 47,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2604.14149 | https://paperswithcode.co/api/v1/papers/arxiv/2604.14149?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.06597 | https://paperswithcode.co/api/v1/papers/arxiv/2502.06597?include_resources=true | 200 | true | 86988 | Continual Release Moment Estimation with Differential Privacy | https://arxiv.org/abs/2502.06597 | [] | [] | [] | [] | [] |
2509.16820 | https://paperswithcode.co/api/v1/papers/arxiv/2509.16820?include_resources=true | 200 | true | 86689 | DISCO: Disentangled Communication Steering for Large Language Models | https://arxiv.org/abs/2509.16820 | [] | [] | [] | [] | [] |
2511.01197 | https://paperswithcode.co/api/v1/papers/arxiv/2511.01197?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2512.03453 | https://paperswithcode.co/api/v1/papers/arxiv/2512.03453?include_resources=true | 200 | true | 64179 | GeoVideo: Introducing Geometric Regularization into Video Generation Model | https://arxiv.org/abs/2512.03453 | [] | [] | [] | [] | [] |
2505.23719 | https://paperswithcode.co/api/v1/papers/arxiv/2505.23719?include_resources=true | 200 | true | 50141 | TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning | https://arxiv.org/abs/2505.23719 | [
{
"url": "https://github.com/nx-ai/tirex",
"owner": "nx-ai",
"name": "tirex",
"stars": 224,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2505.22643 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22643?include_resources=true | 200 | true | 85996 | Spiral: Semantic-Aware Progressive LiDAR Scene Generation | https://arxiv.org/abs/2505.22643 | [] | [] | [] | [] | [] |
2506.10128 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10128?include_resources=true | 200 | true | 50984 | ViCrit: A Verifiable Reinforcement Learning Proxy Task for Visual Perception in VLMs | https://arxiv.org/abs/2506.10128 | [
{
"url": "https://github.com/si0wang/vicrit",
"owner": "si0wang",
"name": "ViCrit",
"stars": 24,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2601.22623 | https://paperswithcode.co/api/v1/papers/arxiv/2601.22623?include_resources=true | 200 | true | 61750 | SYMPHONY: Synergistic Multi-agent Planning with Heterogeneous Language Model Assembly | https://arxiv.org/abs/2601.22623 | [] | [] | [] | [] | [] |
2506.10609 | https://paperswithcode.co/api/v1/papers/arxiv/2506.10609?include_resources=true | 200 | true | 87428 | MSTAR: Box-free Multi-query Scene Text Retrieval with Attention Recycling | https://arxiv.org/abs/2506.10609 | [
{
"url": "https://github.com/yingift/mstar",
"owner": "yingift",
"name": "mstar",
"stars": 10,
"is_official": true,
"source": "neurips2025_import"
}
] | [] | [] | [] | [] |
2506.06298 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06298?include_resources=true | 200 | true | 86432 | Pairwise Calibrated Rewards for Pluralistic Alignment | https://arxiv.org/abs/2506.06298 | [] | [] | [] | [] | [] |
2507.01513 | https://paperswithcode.co/api/v1/papers/arxiv/2507.01513?include_resources=true | 200 | true | 86594 | SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism | https://arxiv.org/abs/2507.01513 | [] | [] | [] | [] | [] |
2505.21494 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21494?include_resources=true | 200 | true | 49952 | Adversarial Attacks against Closed-Source MLLMs via Feature Optimal Alignment | https://arxiv.org/abs/2505.21494 | [
{
"url": "https://github.com/jiaxiaojunqaq/foa-attack",
"owner": "jiaxiaojunQAQ",
"name": "FOA-Attack",
"stars": 42,
"is_official": true,
"source": "links_json"
}
] | [] | [] | [] | [] |
2509.15123 | https://paperswithcode.co/api/v1/papers/arxiv/2509.15123?include_resources=true | 200 | true | 52881 | RGB-Only Supervised Camera Parameter Optimization in Dynamic Scenes | https://arxiv.org/abs/2509.15123 | [] | [] | [] | [] | [] |
2505.22109 | https://paperswithcode.co/api/v1/papers/arxiv/2505.22109?include_resources=true | 200 | true | 72592 | The quest for the GRAph Level autoEncoder (GRALE) | https://arxiv.org/abs/2505.22109 | [] | [] | [] | [] | [] |
2507.06366 | https://paperswithcode.co/api/v1/papers/arxiv/2507.06366?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2502.04979 | https://paperswithcode.co/api/v1/papers/arxiv/2502.04979?include_resources=true | 200 | true | 86936 | Prompt Tuning Decision Transformers with Structured and Scalable Bandits | https://arxiv.org/abs/2502.04979 | [] | [] | [] | [] | [] |
2506.08365 | https://paperswithcode.co/api/v1/papers/arxiv/2506.08365?include_resources=true | 200 | true | 86336 | AlphaFold Database Debiasing for Robust Inverse Folding | https://arxiv.org/abs/2506.08365 | [] | [] | [] | [] | [] |
2502.20432 | https://paperswithcode.co/api/v1/papers/arxiv/2502.20432?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2412.11979 | https://paperswithcode.co/api/v1/papers/arxiv/2412.11979?include_resources=true | 200 | true | 86365 | AlphaZero Neural Scaling and Zipf's Law: a Tale of Board Games and Power Laws | https://arxiv.org/abs/2412.11979 | [] | [] | [] | [] | [] |
2509.20733 | https://paperswithcode.co/api/v1/papers/arxiv/2509.20733?include_resources=true | 200 | true | 86622 | PALQO: Physics-informed model for Accelerating Large-scale Quantum Optimization | https://arxiv.org/abs/2509.20733 | [] | [] | [] | [] | [] |
2511.10859 | https://paperswithcode.co/api/v1/papers/arxiv/2511.10859?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.14069 | https://paperswithcode.co/api/v1/papers/arxiv/2505.14069?include_resources=true | 200 | true | 87223 | Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning | https://arxiv.org/abs/2505.14069 | [] | [] | [] | [] | [] |
2505.21297 | https://paperswithcode.co/api/v1/papers/arxiv/2505.21297?include_resources=true | 200 | true | 49934 | rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset | https://arxiv.org/abs/2505.21297 | [
{
"url": "https://github.com/microsoft/rstar",
"owner": "microsoft",
"name": "rStar",
"stars": 1372,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.16217 | https://paperswithcode.co/api/v1/papers/arxiv/2505.16217?include_resources=true | 200 | true | 86507 | Reward-Aware Proto-Representations in Reinforcement Learning | https://arxiv.org/abs/2505.16217 | [] | [] | [] | [] | [] |
2512.07884 | https://paperswithcode.co/api/v1/papers/arxiv/2512.07884?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2401.13530 | https://paperswithcode.co/api/v1/papers/arxiv/2401.13530?include_resources=true | 200 | true | 87414 | Continuous-time Riemannian SGD and SVRG Flows on Wasserstein Probabilistic Space | https://arxiv.org/abs/2401.13530 | [] | [] | [] | [] | [] |
2503.14905 | https://paperswithcode.co/api/v1/papers/arxiv/2503.14905?include_resources=true | 200 | true | 46368 | Spot the Fake: Large Multimodal Model-Based Synthetic Image Detection with Artifact Explanation | https://arxiv.org/abs/2503.14905 | [
{
"url": "https://github.com/opendatalab/fakevlm",
"owner": "opendatalab",
"name": "FakeVLM",
"stars": 100,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.19601 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19601?include_resources=true | 200 | true | 86763 | Preference Optimization by Estimating the Ratio of the Data Distribution | https://arxiv.org/abs/2505.19601 | [] | [] | [] | [] | [] |
2510.19506 | https://paperswithcode.co/api/v1/papers/arxiv/2510.19506?include_resources=true | 200 | true | 66036 | Lookahead Routing for Large Language Models | https://arxiv.org/abs/2510.19506 | [
{
"url": "https://github.com/huangcb01/lookahead-routing",
"owner": "huangcb01",
"name": "lookahead-routing",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2506.06215 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06215?include_resources=true | 200 | true | 72195 | Corrector Sampling in Language Models | https://arxiv.org/abs/2506.06215 | [] | [] | [] | [] | [] |
2504.21561 | https://paperswithcode.co/api/v1/papers/arxiv/2504.21561?include_resources=true | 200 | true | 48268 | Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuning | https://arxiv.org/abs/2504.21561v3 | [] | [
{
"url": "https://sport-agents.github.io/",
"is_official": true
},
{
"url": "https://sport-agents.github.io",
"is_official": true
}
] | [] | [] | [] |
2510.15501 | https://paperswithcode.co/api/v1/papers/arxiv/2510.15501?include_resources=true | 200 | true | 66254 | DeceptionBench: A Comprehensive Benchmark for AI Deception Behaviors in Real-world Scenarios | https://arxiv.org/abs/2510.15501 | [
{
"url": "https://github.com/Aries-iai/DeceptionBench",
"owner": "Aries-iai",
"name": "DeceptionBench",
"stars": 0,
"is_official": true,
"source": "hf_api"
}
] | [] | [] | [] | [] |
2503.15477 | https://paperswithcode.co/api/v1/papers/arxiv/2503.15477?include_resources=true | 200 | true | 46401 | What Makes a Reward Model a Good Teacher? An Optimization Perspective | https://arxiv.org/abs/2503.15477 | [
{
"url": "https://github.com/princeton-pli/what-makes-good-rm",
"owner": "princeton-pli",
"name": "what-makes-good-rm",
"stars": 41,
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"source": "links_json"
}
] | [] | [] | [] | [] |
2603.07162 | https://paperswithcode.co/api/v1/papers/arxiv/2603.07162?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2510.16511 | https://paperswithcode.co/api/v1/papers/arxiv/2510.16511?include_resources=true | 200 | true | 66219 | Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection | https://arxiv.org/abs/2510.16511 | [] | [] | [] | [] | [] |
2503.09707 | https://paperswithcode.co/api/v1/papers/arxiv/2503.09707?include_resources=true | 200 | true | 86054 | Revisiting Semi-Supervised Learning in the Era of Foundation Models | https://arxiv.org/abs/2503.09707 | [] | [] | [] | [] | [] |
2504.21659 | https://paperswithcode.co/api/v1/papers/arxiv/2504.21659?include_resources=true | 200 | true | 48271 | Ada-R1: Hybrid-CoT via Bi-Level Adaptive Reasoning Optimization | https://arxiv.org/abs/2504.21659v2 | [
{
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"owner": "StarDewXXX",
"name": "AdaR1",
"stars": 20,
"is_official": true,
"source": "ai_extraction"
}
] | [] | [] | [] | [] |
2505.18193 | https://paperswithcode.co/api/v1/papers/arxiv/2505.18193?include_resources=true | 200 | true | 87418 | Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry | https://arxiv.org/abs/2505.18193 | [] | [] | [] | [] | [] |
2503.12919 | https://paperswithcode.co/api/v1/papers/arxiv/2503.12919?include_resources=true | 200 | true | 85757 | Continuous Simplicial Neural Networks | https://arxiv.org/abs/2503.12919 | [] | [] | [] | [] | [] |
2505.19807 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19807?include_resources=true | 200 | true | 87235 | Density Ratio-Free Doubly Robust Proxy Causal Learning | https://arxiv.org/abs/2505.19807 | [] | [] | [] | [] | [] |
2506.04497 | https://paperswithcode.co/api/v1/papers/arxiv/2506.04497?include_resources=true | 200 | true | 86167 | Maximizing the Value of Predictions in Control: Accuracy Is Not Enough | https://arxiv.org/abs/2506.04497 | [] | [] | [] | [] | [] |
2510.18353 | https://paperswithcode.co/api/v1/papers/arxiv/2510.18353?include_resources=true | 200 | true | 66109 | Ranking-based Preference Optimization for Diffusion Models from Implicit
User Feedback | https://arxiv.org/abs/2510.18353 | [
{
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"owner": "basiclab",
"name": "DiffusionDRO",
"stars": 0,
"is_official": true,
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}
] | [] | [] | [] | [] |
2506.02961 | https://paperswithcode.co/api/v1/papers/arxiv/2506.02961?include_resources=true | 200 | true | 72325 | FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large
Language Models | https://arxiv.org/abs/2506.02961 | [] | [] | [] | [] | [] |
2505.19713 | https://paperswithcode.co/api/v1/papers/arxiv/2505.19713?include_resources=true | 200 | true | 72718 | CAD-Coder: Text-to-CAD Generation with Chain-of-Thought and Geometric
Reward | https://arxiv.org/abs/2505.19713 | [] | [] | [] | [] | [] |
2506.01480 | https://paperswithcode.co/api/v1/papers/arxiv/2506.01480?include_resources=true | 200 | true | 50385 | Unlocking Aha Moments via Reinforcement Learning: Advancing Collaborative Visual Comprehension and Generation | https://arxiv.org/abs/2506.01480 | [
{
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2506.07497 | https://paperswithcode.co/api/v1/papers/arxiv/2506.07497?include_resources=true | 200 | true | 72142 | Genesis: Multimodal Driving Scene Generation with Spatio-Temporal and
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2506.06501 | https://paperswithcode.co/api/v1/papers/arxiv/2506.06501?include_resources=true | 200 | true | 86742 | Optimal Rates in Continual Linear Regression via Increasing Regularization | https://arxiv.org/abs/2506.06501 | [] | [] | [] | [] | [] |
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2412.05095 | https://paperswithcode.co/api/v1/papers/arxiv/2412.05095?include_resources=true | 200 | true | 41135 | SoPo: Text-to-Motion Generation Using Semi-Online Preference Optimization | https://arxiv.org/abs/2412.05095 | [
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2511.00833 | https://paperswithcode.co/api/v1/papers/arxiv/2511.00833?include_resources=true | 404 | false | null | null | null | null | null | null | null | null |
2505.09663 | https://paperswithcode.co/api/v1/papers/arxiv/2505.09663?include_resources=true | 200 | true | 86826 | Analog Foundation Models | https://arxiv.org/abs/2505.09663 | [
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2506.11777 | https://paperswithcode.co/api/v1/papers/arxiv/2506.11777?include_resources=true | 200 | true | 72006 | Self-supervised Learning of Echocardiographic Video Representations via
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