✨RbtAct: Rebuttal as Supervision for Actionable Review Feedback Generation

📝 Summary:
Researchers developed RbtAct, a method that uses rebuttal responses to improve the actionability of AI-generated peer-review feedback by training a language model to produce specific, implementable co...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09723
• PDF: https://arxiv.org/pdf/2603.09723
• Github: https://github.com/formula12/RbtAct

✨ Datasets citing this paper:
• https://huggingface.co/datasets/shwu22/RMR-75K

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

📝 Summary:
V2M-Zero enables video-to-music generation with improved temporal alignment by using modality-specific event curves derived from pretrained encoders, achieving superior audio quality and synchronizati...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11042
• PDF: https://arxiv.org/pdf/2603.11042
• Project Page: https://genjib.github.io/v2m_zero/
• Github: https://genjib.github.io/v2m_zero/

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams

📝 Summary:
OAKS is a new benchmark to test how LLMs adapt to real-time, evolving information streams. Current models struggle significantly, showing delays and distraction in tracking dynamic knowledge.

🔹 Publication Date: Published on Mar 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.07392
• PDF: https://arxiv.org/pdf/2603.07392
• Github: https://github.com/kaistAI/OAKS

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨CodePercept: Code-Grounded Visual STEM Perception for MLLMs

📝 Summary:
MLLMs struggle with STEM visual reasoning due to perceptual limitations rather than reasoning deficiencies, and enhancing perception through code-as-perception paradigms improves performance. AI-gener...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10757
• PDF: https://arxiv.org/pdf/2603.10757
• Github: https://github.com/TongkunGuan/Qwen-CodePercept

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨MA-EgoQA: Question Answering over Egocentric Videos from Multiple Embodied Agents

📝 Summary:
Multi-agent systems require understanding multiple long-horizon egocentric videos simultaneously, necessitating new benchmarks and models for system-level comprehension. AI-generated summary As embodi...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09827
• PDF: https://arxiv.org/pdf/2603.09827
• Project Page: https://ma-egoqa.github.io/
• Github: https://github.com/KangsanKim07/MA-EgoQA

✨ Datasets citing this paper:
• https://huggingface.co/datasets/KangsanKim71/MA-EgoQA

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Any to Full: Prompting Depth Anything for Depth Completion in One Stage

📝 Summary:
A novel one-stage depth completion framework that uses scale-prompting adaptation of pretrained monocular depth estimation models to handle varying depth sparsity and irregular distributions more effi...

🔹 Publication Date: Published on Mar 5

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.05711
• PDF: https://arxiv.org/pdf/2603.05711

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨LLM2Vec-Gen: Generative Embeddings from Large Language Models

📝 Summary:
LLM2Vec-Gen introduces a self-supervised method for text embedding that represents model responses through trainable special tokens, achieving superior performance on MTEB while reducing harmful conte...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10913
• PDF: https://arxiv.org/pdf/2603.10913
• Project Page: https://mcgill-nlp.github.io/llm2vec-gen/
• Github: https://github.com/McGill-NLP/llm2vec-gen

🔹 Models citing this paper:
• https://huggingface.co/McGill-NLP/LLM2Vec-Gen-Qwen3-06B
• https://huggingface.co/McGill-NLP/LLM2Vec-Gen-Qwen3-17B
• https://huggingface.co/McGill-NLP/LLM2Vec-Gen-Qwen3-4B

==================================

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✨TADA: A Generative Framework for Speech Modeling via Text-Acoustic Dual Alignment

📝 Summary:
A novel tokenization scheme synchronizes acoustic features with text tokens in TTS systems, enabling unified modeling and reduced hallucinations through flow matching and text-only guidance. AI-genera...

🔹 Publication Date: Published on Feb 26

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2602.23068
• PDF: https://arxiv.org/pdf/2602.23068
• Project Page: https://www.hume.ai/blog/opensource-tada
• Github: https://github.com/HumeAI/tada

🔹 Models citing this paper:
• https://huggingface.co/HumeAI/tada-1b
• https://huggingface.co/HumeAI/tada-3b-ml
• https://huggingface.co/HumeAI/tada-codec

✨ Spaces citing this paper:
• https://huggingface.co/spaces/HumeAI/tada

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Flash-KMeans: Fast and Memory-Efficient Exact K-Means

📝 Summary:
Flash-kmeans enables efficient online k-means clustering on GPUs through novel kernel-level optimizations that eliminate I/O bottlenecks and atomic write contention. AI-generated summary k-means has h...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09229
• PDF: https://arxiv.org/pdf/2603.09229
• Github: https://github.com/svg-project/flash-kmeans

==================================

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✨ReMix: Reinforcement routing for mixtures of LoRAs in LLM finetuning

📝 Summary:
Researchers address imbalance in routing weights of Mixture-of-LoRAs models by proposing Reinforcement Routing (ReMix), which uses non-learnable weights and reinforcement learning techniques to improv...

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10160
• PDF: https://arxiv.org/pdf/2603.10160

==================================

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✨Prism-Δ: Differential Subspace Steering for Prompt Highlighting in Large Language Models

📝 Summary:
PRISM-Δ extracts discriminative steering directions by decomposing cross-covariance differences, uses softplus weights for attention heads, and extends to value representations for improved long-conte...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10705
• PDF: https://arxiv.org/pdf/2603.10705
• Project Page: https://yuyaoge.github.io/PRISM-DELTA/
• Github: https://github.com/YuyaoGe/PRISM-DELTA

==================================

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✨In-Context Reinforcement Learning for Tool Use in Large Language Models

📝 Summary:
In-Context Reinforcement Learning ICRL is an RL-only framework for LLMs to use external tools, eliminating costly supervised fine-tuning. It teaches tool use through in-context examples during training, gradually reducing them. ICRL proves to be a scalable, data-efficient, and state-of-the-art ap...

🔹 Publication Date: Published on Mar 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08068
• PDF: https://arxiv.org/pdf/2603.08068
• Github: https://github.com/applese233/ICRL

==================================

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✨Hindsight Credit Assignment for Long-Horizon LLM Agents

📝 Summary:
HCAPO improves credit assignment in long-horizon LLM agents by using hindsight reasoning to refine Q-values and a multi-scale advantage mechanism. It significantly outperforms state-of-the-art methods, boosting success rates on benchmarks like WebShop and ALFWorld. This enhances exploration and c...

🔹 Publication Date: Published on Mar 7

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.08754
• PDF: https://arxiv.org/pdf/2603.08754

==================================

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#LLMAgents #ReinforcementLearning #AI #MachineLearning #HindsightReasoning

✨UniCom: Unified Multimodal Modeling via Compressed Continuous Semantic Representations

📝 Summary:
UniCom unifies multimodal understanding and generation via compressed continuous semantic representations. It resolves issues with discrete tokenizers and unstable continuous modeling by efficiently reducing channel dimensions. This yields state-of-the-art generation, superior controllability, an...

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10702
• PDF: https://arxiv.org/pdf/2603.10702
• Project Page: https://miazhao7708.github.io/UniComPage/

==================================

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#MultimodalAI #GenerativeAI #DeepLearning #AIResearch #SemanticRepresentations

✨Lost in Backpropagation: The LM Head is a Gradient Bottleneck

📝 Summary:
The softmax bottleneck in neural LMs is a critical optimization bottleneck, not just an expressivity issue. The rank-D output layer suppresses 95-99% of gradient norm, leading to suboptimal updates and inefficient training. This necessitates new LM head designs.

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10145
• PDF: https://arxiv.org/pdf/2603.10145

==================================

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#LLM #DeepLearning #Optimization #NeuralNetworks #GradientBottleneck

✨StyleVLA: Driving Style-Aware Vision Language Action Model for Autonomous Driving

📝 Summary:
StyleVLA is a physics-informed VLA model that generates diverse, style-aware, and kinematically plausible driving trajectories. It uses a hybrid loss and a large dataset, outperforming proprietary models like Gemini-3-Pro on specialized driving tasks.

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.09482
• PDF: https://arxiv.org/pdf/2603.09482

==================================

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#AutonomousDriving #VLA #AI #DeepLearning #Robotics

✨Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning

📝 Summary:
Causal Concept Graphs identify causal relationships between concepts in LLMs using sparse autoencoders and differentiable structure learning. This method significantly improves causal fidelity for multi-step reasoning over prior techniques, yielding sparse and stable graphs.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10377
• PDF: https://arxiv.org/pdf/2603.10377

==================================

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#CausalAI #LLMs #MachineLearning #GraphLearning #ExplainableAI

✨According to Me: Long-Term Personalized Referential Memory QA

📝 Summary:
ATM-Bench is a new benchmark for multimodal multi-source personalized referential memory QA, addressing limitations of existing dialogue-focused benchmarks. It includes 4 years of personal data and introduces Schema-Guided Memory SGM. Current AI systems perform poorly under 20 percent on hard set...

🔹 Publication Date: Published on Mar 2

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.01990
• PDF: https://arxiv.org/pdf/2603.01990
• Project Page: https://atmbench.github.io/
• Github: https://github.com/JingbiaoMei/ATM-Bench

✨ Datasets citing this paper:
• https://huggingface.co/datasets/Jingbiao/ATM-Bench

==================================

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#AI #QuestionAnswering #LongTermMemory #MachineLearning #Benchmark

✨ID-LoRA: Identity-Driven Audio-Video Personalization with In-Context LoRA

📝 Summary:
ID-LoRA jointly generates visual appearance and voice with a single model, improving personalization. It uses in-context LoRA adaptation and identity guidance to preserve speaker characteristics. This outperforms existing methods in human preference for voice and style similarity.

🔹 Publication Date: Published on Mar 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.10256
• PDF: https://arxiv.org/pdf/2603.10256
• Project Page: https://id-lora.github.io/
• Github: https://github.com/ID-LoRA/ID-LoRA

==================================

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#GenerativeAI #AudioVisual #LoRA #Personalization #DeepLearning

✨COMIC: Agentic Sketch Comedy Generation

📝 Summary:
An AI system generates comedic videos similar to sketch shows. It employs agent-based optimization and LLM critics, trained on YouTube comedy, to evaluate humor. This system produces content approaching professional sketch quality.

🔹 Publication Date: Published on Mar 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.11048
• PDF: https://arxiv.org/pdf/2603.11048
• Project Page: https://susunghong.github.io/COMIC/
• Github: https://susunghong.github.io/COMIC/

==================================

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#AI #GenerativeAI #SketchComedy #LLMs #ComputationalCreativity

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