✨CLINIC: Evaluating Multilingual Trustworthiness in Language Models for Healthcare

📝 Summary:
CLINIC is a multilingual benchmark evaluating language model trustworthiness in healthcare across 15 languages and five dimensions. It finds that LMs struggle with factual correctness, demonstrate bias, and are vulnerable to privacy breaches and attacks. This work highlights shortcomings to impro...

🔹 Publication Date: Published on Dec 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11437
• PDF: https://arxiv.org/pdf/2512.11437

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#AI #HealthcareAI #LLM #AISafety #MultilingualAI

✨Causal Judge Evaluation: Calibrated Surrogate Metrics for LLM Systems

📝 Summary:
CJE improves LLM-as-judge evaluation by fixing statistical issues like uncalibrated scores and poor confidence intervals. It achieves 99% ranking accuracy at 14x lower cost by calibrating a cheaper judge with 5% oracle labels.

🔹 Publication Date: Published on Dec 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11150
• PDF: https://arxiv.org/pdf/2512.11150
• Project Page: https://www.cimolabs.com/cje
• Github: https://github.com/cimo-labs/cje

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#LLMs #AIEvaluation #MachineLearning #DataScience #NLP

✨Particulate: Feed-Forward 3D Object Articulation

📝 Summary:
Particulate is a feed-forward method using a transformer network to infer articulated 3D structures from single static meshes, achieving faster and more accurate results than prior approaches. AI-gene...

🔹 Publication Date: Published on Dec 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11798
• PDF: https://arxiv.org/pdf/2512.11798

🔹 Models citing this paper:
• https://huggingface.co/rayli/Particulate

✨ Spaces citing this paper:
• https://huggingface.co/spaces/rayli/particulate

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✨Fast-FoundationStereo: Real-Time Zero-Shot Stereo Matching

📝 Summary:
Fast-FoundationStereo enables real-time zero-shot stereo matching. It uses knowledge distillation, neural architecture search, and structured pruning to achieve this. The model runs over 10x faster than previous models while maintaining accuracy, setting a new state-of-the-art.

🔹 Publication Date: Published on Dec 11

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11130
• PDF: https://arxiv.org/pdf/2512.11130
• Project Page: https://nvlabs.github.io/Fast-FoundationStereo/
• Github: https://github.com/NVlabs/Fast-FoundationStereo

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✨Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit

📝 Summary:
Sparse autoencoders SAEs create interpretable, cost-effective embeddings where dimensions map to concepts. These SAE embeddings outperform LLMs and dense embeddings for large-scale text analysis, offering better control for tasks like bias identification and dataset comparison.

🔹 Publication Date: Published on Dec 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.10092
• PDF: https://arxiv.org/pdf/2512.10092
• Project Page: https://interp-embed.com
• Github: https://github.com/nickjiang2378/interp_embed

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✨Openpi Comet: Competition Solution For 2025 BEHAVIOR Challenge

📝 Summary:
The Openpi Comet solution for the 2025 BEHAVIOR Challenge addresses household tasks using pre-training and post-training. It achieved a close second place, significantly outperforming other submissions, demonstrating the scaling power of these methods.

🔹 Publication Date: Published on Dec 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2512.10071
• PDF: https://arxiv.org/pdf/2512.10071
• Github: https://github.com/mli0603/openpi-comet

🔹 Models citing this paper:
• https://huggingface.co/sunshk/comet_submission

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✨MentraSuite: Post-Training Large Language Models for Mental Health Reasoning and Assessment

📝 Summary:
MentraSuite, a unified framework, advances reliable mental health reasoning using Mindora, a post-trained model with hybrid SFT-RL, evaluated via MentraBench, a benchmark assessing task performance an...

🔹 Publication Date: Published on Dec 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.09636
• PDF: https://arxiv.org/pdf/2512.09636
• Github: https://github.com/elsa66666/MentraSuite

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✨Error-Free Linear Attention is a Free Lunch: Exact Solution from Continuous-Time Dynamics

📝 Summary:
Error-Free Linear Attention (EFLA) is a stable, parallelizable, and theoretically sound linear-time attention mechanism that outperforms DeltaNet in language modeling and downstream tasks. AI-generate...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12602
• PDF: https://arxiv.org/pdf/2512.12602
• Github: https://github.com/declare-lab/EFLA

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✨NL2Repo-Bench: Towards Long-Horizon Repository Generation Evaluation of Coding Agents

📝 Summary:
NL2Repo Bench evaluates long-horizon software development capabilities of coding agents by assessing their ability to generate complete Python libraries from natural-language requirements. AI-generate...

🔹 Publication Date: Published on Dec 14

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12730
• PDF: https://arxiv.org/pdf/2512.12730
• Project Page: https://github.com/multimodal-art-projection/NL2RepoBench
• Github: https://github.com/multimodal-art-projection/NL2RepoBench

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✨LongVie 2: Multimodal Controllable Ultra-Long Video World Model

📝 Summary:
LongVie 2, an end-to-end autoregressive framework, enhances controllability, visual quality, and temporal consistency in video world models through three progressive training stages. AI-generated summ...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13604
• PDF: https://arxiv.org/pdf/2512.13604
• Project Page: https://vchitect.github.io/LongVie2-project/
• Github: https://github.com/Vchitect/LongVie

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✨V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions

📝 Summary:
The V-REX evaluation suite assesses vision-language models' multi-step reasoning and exploration capabilities through a Chain-of-Questions framework, revealing their strengths and weaknesses in planni...

🔹 Publication Date: Published on Dec 12

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11995
• PDF: https://arxiv.org/pdf/2512.11995
• Github: https://github.com/tianyi-lab/VREX

✨ Datasets citing this paper:
• https://huggingface.co/datasets/umd-zhou-lab/V-REX

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✨Image Diffusion Preview with Consistency Solver

📝 Summary:
Diffusion Preview uses ConsistencySolver, a high-order trainable solver, to improve quality and consistency in low-step image generation, enhancing interactive user experiences. AI-generated summary T...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13592
• PDF: https://arxiv.org/pdf/2512.13592
• Github: https://github.com/G-U-N/consolver

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

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✨Video Reality Test: Can AI-Generated ASMR Videos fool VLMs and Humans?

📝 Summary:
The Video Reality Test benchmark evaluates the realism and detection of AI-generated ASMR videos with audio, revealing that even the best models can deceive VLMs and humans, highlighting limitations i...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13281
• PDF: https://arxiv.org/pdf/2512.13281
• Project Page: https://video-reality-test.github.io/
• Github: https://github.com/video-reality-test/video-reality-test

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✨Aesthetic Alignment Risks Assimilation: How Image Generation and Reward Models Reinforce Beauty Bias and Ideological "Censorship"

📝 Summary:
State-of-the-art image generation and reward models exhibit bias towards conventional aesthetics, often failing to produce anti-aesthetic images as requested, thus compromising user autonomy and aesth...

🔹 Publication Date: Published on Dec 9

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.11883
• PDF: https://arxiv.org/pdf/2512.11883

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✨KlingAvatar 2.0 Technical Report

📝 Summary:
KlingAvatar 2.0 addresses inefficiencies in generating long-duration, high-resolution videos by using a spatio-temporal cascade framework with a Co-Reasoning Director and Negative Director for improve...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13313
• PDF: https://arxiv.org/pdf/2512.13313
• Project Page: https://app.klingai.com/global/ai-human/image/new/

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✨QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management

📝 Summary:
QwenLong-L1.5 enhances long-context reasoning through data synthesis, stabilized reinforcement learning, and memory-augmented architecture, achieving superior performance on benchmarks and general dom...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.12967
• PDF: https://arxiv.org/pdf/2512.12967

🔹 Models citing this paper:
• https://huggingface.co/Tongyi-Zhiwen/QwenLong-L1.5-30B-A3B

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✨START: Spatial and Textual Learning for Chart Understanding

📝 Summary:
START enhances multimodal large language models by integrating spatial and textual learning through chart-element grounding and chart-to-code generation, improving chart understanding and performance ...

🔹 Publication Date: Published on Dec 8

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.07186
• PDF: https://arxiv.org/pdf/2512.07186
• Github: https://github.com/dragonlzm/START

🔹 Models citing this paper:
• https://huggingface.co/zhuomingliu/START

✨ Datasets citing this paper:
• https://huggingface.co/datasets/zhuomingliu/CS-Bench
• https://huggingface.co/datasets/zhuomingliu/START-Dataset
• https://huggingface.co/datasets/zhuomingliu/START_eval

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✨Memory in the Age of AI Agents

📝 Summary:
This survey provides an updated overview of agent memory research, distinguishing its forms, functions, and dynamics, and highlights emerging research directions. AI-generated summary Memory has emerg...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13564
• PDF: https://arxiv.org/pdf/2512.13564

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

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✨ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding

📝 Summary:
ReFusion, a novel masked diffusion model, improves performance and efficiency by using slot-based parallel decoding, achieving superior results compared to autoregressive models and traditional masked...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13586
• PDF: https://arxiv.org/pdf/2512.13586
• Github: https://github.com/ML-GSAI/ReFusion

🔹 Models citing this paper:
• https://huggingface.co/GSAI-ML/ReFusion

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✨Spatial-Aware VLA Pretraining through Visual-Physical Alignment from Human Videos

📝 Summary:
A Spatial-Aware VLA Pretraining paradigm improves 3D spatial understanding in robots by aligning 2D visual inputs with 3D actions using dual-encoder architecture with a 3D visual encoder. AI-generated...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13080
• PDF: https://arxiv.org/pdf/2512.13080
• Project Page: https://beingbeyond.github.io/VIPA-VLA/
• Github: https://beingbeyond.github.io/VIPA-VLA

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✨Toward Ambulatory Vision: Learning Visually-Grounded Active View Selection

📝 Summary:
VG-AVS, a task and framework fine-tunes VLMs to select the most informative next viewpoint for visual question answering, enhancing performance and generalization. AI-generated summary Vision Language...

🔹 Publication Date: Published on Dec 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.13250
• PDF: https://arxiv.org/pdf/2512.13250
• Project Page: https://active-view-selection.github.io
• Github: https://github.com/KAIST-Visual-AI-Group/VG-AVS

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