✨IceCache: Memory-efficient KV-cache Management for Long-Sequence LLMs
📝 Summary:
IceCache is a novel KV cache management strategy for long-sequence LLMs that uses semantic token clustering with PagedAttention. It significantly improves memory efficiency while maintaining high accuracy, reducing the KV cache budget by 75% and outperforming other offloading methods.
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10539
• PDF: https://arxiv.org/pdf/2604.10539
• Project Page: https://yuzhenmao.github.io/IceCache/
• Github: https://github.com/yuzhenmao/IceCache
==================================
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📝 Summary:
IceCache is a novel KV cache management strategy for long-sequence LLMs that uses semantic token clustering with PagedAttention. It significantly improves memory efficiency while maintaining high accuracy, reducing the KV cache budget by 75% and outperforming other offloading methods.
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10539
• PDF: https://arxiv.org/pdf/2604.10539
• Project Page: https://yuzhenmao.github.io/IceCache/
• Github: https://github.com/yuzhenmao/IceCache
==================================
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✨ATANT: An Evaluation Framework for AI Continuity
📝 Summary:
ATANT presents an open framework for evaluating AI system continuity through a 10-checkpoint methodology using a 250-story corpus across 6 life domains, achieving 100% accuracy in cumulative testing. ...
🔹 Publication Date: Published on Apr 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.06710
• PDF: https://arxiv.org/pdf/2604.06710
• Project Page: https://kenoticlabs.com
• Github: https://github.com/Kenotic-Labs/ATANT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Kenotic-Labs/ATANTV1.0-corpus
==================================
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📝 Summary:
ATANT presents an open framework for evaluating AI system continuity through a 10-checkpoint methodology using a 250-story corpus across 6 life domains, achieving 100% accuracy in cumulative testing. ...
🔹 Publication Date: Published on Apr 8
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.06710
• PDF: https://arxiv.org/pdf/2604.06710
• Project Page: https://kenoticlabs.com
• Github: https://github.com/Kenotic-Labs/ATANT
✨ Datasets citing this paper:
• https://huggingface.co/datasets/Kenotic-Labs/ATANTV1.0-corpus
==================================
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✨Audio-Omni: Extending Multi-modal Understanding to Versatile Audio Generation and Editing
📝 Summary:
Audio-Omni presents the first framework unifying audio generation and editing across diverse audio domains. It combines a multimodal LLM and diffusion transformer, introduces AudioEdit, and achieves state-of-the-art results.
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10708
• PDF: https://arxiv.org/pdf/2604.10708
• Project Page: https://zeyuet.github.io/Audio-Omni/
• Github: https://github.com/ZeyueT/Audio-Omni
==================================
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📝 Summary:
Audio-Omni presents the first framework unifying audio generation and editing across diverse audio domains. It combines a multimodal LLM and diffusion transformer, introduces AudioEdit, and achieves state-of-the-art results.
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10708
• PDF: https://arxiv.org/pdf/2604.10708
• Project Page: https://zeyuet.github.io/Audio-Omni/
• Github: https://github.com/ZeyueT/Audio-Omni
==================================
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✨Time is Not a Label: Continuous Phase Rotation for Temporal Knowledge Graphs and Agentic Memory
📝 Summary:
RoMem introduces a temporal knowledge graph module that uses semantic speed gates and continuous phase rotation to distinguish persistent from evolving facts, achieving superior performance in tempora...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11544
• PDF: https://arxiv.org/pdf/2604.11544
==================================
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📝 Summary:
RoMem introduces a temporal knowledge graph module that uses semantic speed gates and continuous phase rotation to distinguish persistent from evolving facts, achieving superior performance in tempora...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11544
• PDF: https://arxiv.org/pdf/2604.11544
==================================
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✨Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe
📝 Summary:
On-policy distillation dynamics in large language models depend on compatible thinking patterns between teacher and student models, with successful distillation characterized by alignment on high-prob...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13016
• PDF: https://arxiv.org/pdf/2604.13016
• Github: https://github.com/thunlp/OPD
==================================
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📝 Summary:
On-policy distillation dynamics in large language models depend on compatible thinking patterns between teacher and student models, with successful distillation characterized by alignment on high-prob...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13016
• PDF: https://arxiv.org/pdf/2604.13016
• Github: https://github.com/thunlp/OPD
==================================
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✨Toward Autonomous Long-Horizon Engineering for ML Research
📝 Summary:
AiScientist enables autonomous long-horizon ML research engineering by combining hierarchical orchestration with durable state management, achieving superior performance on benchmark tasks through str...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13018
• PDF: https://arxiv.org/pdf/2604.13018
• Github: https://github.com/AweAI-Team/AiScientist
==================================
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📝 Summary:
AiScientist enables autonomous long-horizon ML research engineering by combining hierarchical orchestration with durable state management, achieving superior performance on benchmark tasks through str...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13018
• PDF: https://arxiv.org/pdf/2604.13018
• Github: https://github.com/AweAI-Team/AiScientist
==================================
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✨SPPO: Sequence-Level PPO for Long-Horizon Reasoning Tasks
📝 Summary:
Sequence-Level PPO addresses instability in long-chain-of-thought reasoning by reformulating the process as a contextual bandit problem with decoupled value functions for improved efficiency. AI-gener...
🔹 Publication Date: Published on Apr 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08865
• PDF: https://arxiv.org/pdf/2604.08865
• Github: https://github.com/sustech-nlp/SPPO
==================================
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📝 Summary:
Sequence-Level PPO addresses instability in long-chain-of-thought reasoning by reformulating the process as a contextual bandit problem with decoupled value functions for improved efficiency. AI-gener...
🔹 Publication Date: Published on Apr 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.08865
• PDF: https://arxiv.org/pdf/2604.08865
• Github: https://github.com/sustech-nlp/SPPO
==================================
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✨Habitat-GS: A High-Fidelity Navigation Simulator with Dynamic Gaussian Splatting
📝 Summary:
Habitat-GS extends Habitat-Sim by integrating 3D Gaussian Splatting for photorealistic rendering and gaussian avatars for dynamic human modeling, enabling improved agent generalization and human-aware...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12626
• PDF: https://arxiv.org/pdf/2604.12626
• Project Page: https://zju3dv.github.io/habitat-gs/
• Github: https://github.com/zju3dv/habitat-gs
✨ Datasets citing this paper:
• https://huggingface.co/datasets/RukawaY/gs_scenes
==================================
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📝 Summary:
Habitat-GS extends Habitat-Sim by integrating 3D Gaussian Splatting for photorealistic rendering and gaussian avatars for dynamic human modeling, enabling improved agent generalization and human-aware...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12626
• PDF: https://arxiv.org/pdf/2604.12626
• Project Page: https://zju3dv.github.io/habitat-gs/
• Github: https://github.com/zju3dv/habitat-gs
✨ Datasets citing this paper:
• https://huggingface.co/datasets/RukawaY/gs_scenes
==================================
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✨Rethinking the Diffusion Model from a Langevin Perspective
📝 Summary:
The article provides a unified Langevin perspective on diffusion models, clarifying their theoretical foundations and connections between different mathematical formulations. AI-generated summary Diff...
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10465
• PDF: https://arxiv.org/pdf/2604.10465
• Project Page: https://iclr-blogposts.github.io/2026/blog/2026/rethinking-diffusion-langevin/
==================================
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📝 Summary:
The article provides a unified Langevin perspective on diffusion models, clarifying their theoretical foundations and connections between different mathematical formulations. AI-generated summary Diff...
🔹 Publication Date: Published on Apr 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10465
• PDF: https://arxiv.org/pdf/2604.10465
• Project Page: https://iclr-blogposts.github.io/2026/blog/2026/rethinking-diffusion-langevin/
==================================
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✨Generative Refinement Networks for Visual Synthesis
📝 Summary:
Generative Refinement Networks introduce a novel visual synthesis approach that combines hierarchical binary quantization with adaptive refinement mechanisms to improve computational efficiency and vi...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13030
• PDF: https://arxiv.org/pdf/2604.13030
• Github: https://github.com/MGenAI/GRN
==================================
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📝 Summary:
Generative Refinement Networks introduce a novel visual synthesis approach that combines hierarchical binary quantization with adaptive refinement mechanisms to improve computational efficiency and vi...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13030
• PDF: https://arxiv.org/pdf/2604.13030
• Github: https://github.com/MGenAI/GRN
==================================
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✨Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation
📝 Summary:
Lightning OPD enables efficient offline on-policy distillation for large language models by enforcing teacher consistency and eliminating the need for live teacher inference servers. AI-generated summ...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13010
• PDF: https://arxiv.org/pdf/2604.13010
==================================
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📝 Summary:
Lightning OPD enables efficient offline on-policy distillation for large language models by enforcing teacher consistency and eliminating the need for live teacher inference servers. AI-generated summ...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13010
• PDF: https://arxiv.org/pdf/2604.13010
==================================
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✨Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
📝 Summary:
Nemotron 3 Super is a 120 billion parameter hybrid Mamba-Attention Mixture-of-Experts model pre-trained in NVFP4 with LatentMoE architecture and MTP layers for accelerated inference, achieving superio...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12374
• PDF: https://arxiv.org/pdf/2604.12374
==================================
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📝 Summary:
Nemotron 3 Super is a 120 billion parameter hybrid Mamba-Attention Mixture-of-Experts model pre-trained in NVFP4 with LatentMoE architecture and MTP layers for accelerated inference, achieving superio...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12374
• PDF: https://arxiv.org/pdf/2604.12374
==================================
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✨Towards Long-horizon Agentic Multimodal Search
📝 Summary:
A novel long-horizon multimodal deep search framework called LMM-Searcher is introduced, featuring a file-based visual representation mechanism and progressive visual loading to handle heterogeneous i...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12890
• PDF: https://arxiv.org/pdf/2604.12890
• Github: https://github.com/RUCAIBox/LMM-Searcher
==================================
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📝 Summary:
A novel long-horizon multimodal deep search framework called LMM-Searcher is introduced, featuring a file-based visual representation mechanism and progressive visual loading to handle heterogeneous i...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12890
• PDF: https://arxiv.org/pdf/2604.12890
• Github: https://github.com/RUCAIBox/LMM-Searcher
==================================
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✨KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance
📝 Summary:
KnowRL is a knowledge-guided reinforcement learning framework that improves reasoning in language models by optimizing compact, interaction-aware guidance subsets through constrained subset search and...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12627
• PDF: https://arxiv.org/pdf/2604.12627
• Github: https://github.com/Hasuer/KnowRL
🔹 Models citing this paper:
• https://huggingface.co/HasuerYu/KnowRL-Nemotron-1.5B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/HasuerYu/KnowRL-KP-Annotations
• https://huggingface.co/datasets/HasuerYu/KnowRL-Train-Data
==================================
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📝 Summary:
KnowRL is a knowledge-guided reinforcement learning framework that improves reasoning in language models by optimizing compact, interaction-aware guidance subsets through constrained subset search and...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12627
• PDF: https://arxiv.org/pdf/2604.12627
• Github: https://github.com/Hasuer/KnowRL
🔹 Models citing this paper:
• https://huggingface.co/HasuerYu/KnowRL-Nemotron-1.5B
✨ Datasets citing this paper:
• https://huggingface.co/datasets/HasuerYu/KnowRL-KP-Annotations
• https://huggingface.co/datasets/HasuerYu/KnowRL-Train-Data
==================================
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✨Self-Adversarial One Step Generation via Condition Shifting
📝 Summary:
APEx enables efficient one-step text-to-image synthesis by eliminating adversarial training through endogenous gradient estimation from flow models, achieving superior quality and speed compared to ex...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12322
• PDF: https://arxiv.org/pdf/2604.12322
• Github: https://github.com/LINs-lab/APEX
==================================
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📝 Summary:
APEx enables efficient one-step text-to-image synthesis by eliminating adversarial training through endogenous gradient estimation from flow models, achieving superior quality and speed compared to ex...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12322
• PDF: https://arxiv.org/pdf/2604.12322
• Github: https://github.com/LINs-lab/APEX
==================================
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✨Lyra 2.0: Explorable Generative 3D Worlds
📝 Summary:
Lyra 2.0 enables large-scale 3D scene creation through persistent video generation that addresses spatial forgetting and temporal drifting issues in long-horizon video models. AI-generated summary Rec...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13036
• PDF: https://arxiv.org/pdf/2604.13036
==================================
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📝 Summary:
Lyra 2.0 enables large-scale 3D scene creation through persistent video generation that addresses spatial forgetting and temporal drifting issues in long-horizon video models. AI-generated summary Rec...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.13036
• PDF: https://arxiv.org/pdf/2604.13036
==================================
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✨LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment
📝 Summary:
General visual foundation models trained without action supervision outperform specialized embodied models and demonstrate superior alignment between visual and physical action spaces compared to pixe...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11689
• PDF: https://github.com/meituan-longcat/LARYBench/blob/main/LARYBench.pdf
• Project Page: https://meituan-longcat.github.io/LARYBench/
• Github: https://meituan-longcat.github.io/LARYBench/
==================================
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📝 Summary:
General visual foundation models trained without action supervision outperform specialized embodied models and demonstrate superior alignment between visual and physical action spaces compared to pixe...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11689
• PDF: https://github.com/meituan-longcat/LARYBench/blob/main/LARYBench.pdf
• Project Page: https://meituan-longcat.github.io/LARYBench/
• Github: https://meituan-longcat.github.io/LARYBench/
==================================
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✨You Only Judge Once: Multi-response Reward Modeling in a Single Forward Pass
📝 Summary:
A multimodal reward model evaluates multiple responses simultaneously through concatenated input and cross-entropy scoring, achieving faster training and superior performance in open-ended generation ...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10966
• PDF: https://arxiv.org/pdf/2604.10966
==================================
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📝 Summary:
A multimodal reward model evaluates multiple responses simultaneously through concatenated input and cross-entropy scoring, achieving faster training and superior performance in open-ended generation ...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.10966
• PDF: https://arxiv.org/pdf/2604.10966
==================================
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✨VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
📝 Summary:
VideoFlexTok enables efficient video representation through variable-length token sequences that capture abstract information first, followed by fine-grained details, allowing for reduced computationa...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12887
• PDF: https://arxiv.org/pdf/2604.12887
• Github: https://github.com/apple/ml-videoflextok
==================================
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📝 Summary:
VideoFlexTok enables efficient video representation through variable-length token sequences that capture abstract information first, followed by fine-grained details, allowing for reduced computationa...
🔹 Publication Date: Published on Apr 14
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.12887
• PDF: https://arxiv.org/pdf/2604.12887
• Github: https://github.com/apple/ml-videoflextok
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✨Seeing Through Touch: Tactile-Driven Visual Localization of Material Regions
📝 Summary:
Deep learning model for tactile localization that uses dense cross-modal feature interactions to identify material properties in images, overcoming limitations of existing methods through enhanced dat...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11579
• PDF: https://arxiv.org/pdf/2604.11579
• Project Page: https://mm.kaist.ac.kr/projects/SeeingThroughTouch/
• Github: https://github.com/kaistmm/SeeingThroughTouch
==================================
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📝 Summary:
Deep learning model for tactile localization that uses dense cross-modal feature interactions to identify material properties in images, overcoming limitations of existing methods through enhanced dat...
🔹 Publication Date: Published on Apr 13
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.11579
• PDF: https://arxiv.org/pdf/2604.11579
• Project Page: https://mm.kaist.ac.kr/projects/SeeingThroughTouch/
• Github: https://github.com/kaistmm/SeeingThroughTouch
==================================
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✨Many-Tier Instruction Hierarchy in LLM Agents
📝 Summary:
Large language model agents require robust instruction conflict resolution mechanisms that can handle arbitrary privilege levels across diverse real-world scenarios, revealing current models' limitati...
🔹 Publication Date: Published on Apr 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09443
• PDF: https://arxiv.org/pdf/2604.09443
• Project Page: https://jhu-clsp.github.io/ManyIH
• Github: https://github.com/JHU-CLSP/ManyIH
✨ Datasets citing this paper:
• https://huggingface.co/datasets/jhu-clsp/ManyIH-Bench
• https://huggingface.co/datasets/jackzhang/ManyIH-Bench
==================================
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📝 Summary:
Large language model agents require robust instruction conflict resolution mechanisms that can handle arbitrary privilege levels across diverse real-world scenarios, revealing current models' limitati...
🔹 Publication Date: Published on Apr 10
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.09443
• PDF: https://arxiv.org/pdf/2604.09443
• Project Page: https://jhu-clsp.github.io/ManyIH
• Github: https://github.com/JHU-CLSP/ManyIH
✨ Datasets citing this paper:
• https://huggingface.co/datasets/jhu-clsp/ManyIH-Bench
• https://huggingface.co/datasets/jackzhang/ManyIH-Bench
==================================
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