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From Segments to Scenes: Temporal Understanding in Autonomous Driving via Vision-Language Model

Intermediate

Kevin Cannons, Saeed Ranjbar Alvar et al.Dec 4arXiv

This paper builds TAD, a brand-new test that checks if AI can understand what happens over time in real driving videos.

#Temporal understanding#Autonomous driving#Vision-language models

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Joint 3D Geometry Reconstruction and Motion Generation for 4D Synthesis from a Single Image

Intermediate

Yanran Zhang, Ziyi Wang et al.Dec 4arXiv

This paper teaches a computer to turn one single picture into a moving 3D scene that stays consistent from every camera angle.

#4D scene generation#single-image to 4D#joint geometry and motion

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Arbitrage: Efficient Reasoning via Advantage-Aware Speculation

Intermediate

Monishwaran Maheswaran, Rishabh Tiwari et al.Dec 4arXiv

ARBITRAGE makes AI solve step-by-step problems faster by only using the big, slow model when it is predicted to truly help.

#speculative decoding#step-level speculative decoding#advantage-aware routing

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EMMA: Efficient Multimodal Understanding, Generation, and Editing with a Unified Architecture

Intermediate

Xin He, Longhui Wei et al.Dec 4arXiv

EMMA is a single AI model that can understand images, write about them, create new images from text, and edit images—all in one unified system.

#EMMA#unified multimodal architecture#32x autoencoder

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EtCon: Edit-then-Consolidate for Reliable Knowledge Editing

Intermediate

Ruilin Li, Yibin Wang et al.Dec 4arXiv

Large language models forget or misuse new facts if you only poke their weights once; EtCon fixes this with a two-step plan.

#knowledge editing#EtCon#TPSFT

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TwinFlow: Realizing One-step Generation on Large Models with Self-adversarial Flows

Intermediate

Zhenglin Cheng, Peng Sun et al.Dec 3arXiv

TwinFlow is a new way to make big image models draw great pictures in just one step instead of 40–100 steps.

#TwinFlow#one-step generation#twin trajectories

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M3DR: Towards Universal Multilingual Multimodal Document Retrieval

Intermediate

Adithya S Kolavi, Vyoman JainDec 3arXiv

The paper introduces M3DR, a way for computers to find the right document image no matter which of 22 languages the query or the document uses.

#multilingual retrieval#multimodal retrieval#document image search

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SPARK: Stepwise Process-Aware Rewards for Reference-Free Reinforcement Learning

Intermediate

Salman Rahman, Sruthi Gorantla et al.Dec 2arXiv

SPARK teaches AI to grade its own steps without needing the right answers written down anywhere.

#SPARK#Process Reward Model#PRM-CoT

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Self-Improving VLM Judges Without Human Annotations

Intermediate

Inna Wanyin Lin, Yushi Hu et al.Dec 2arXiv

The paper shows how a vision-language model (VLM) can train itself to be a fair judge of answers about images without using any human preference labels.

#vision-language model#VLM judge#reward model

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Fairy2i: Training Complex LLMs from Real LLMs with All Parameters in $\{\pm 1, \pm i\}$

Intermediate

Feiyu Wang, Xinyu Tan et al.Dec 2arXiv

Fairy2i turns any pre-trained real-valued Transformer layer into an exactly equivalent complex form, so nothing changes before quantization.

#LLM quantization#complex-valued neural networks#widely-linear transformation

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ReVSeg: Incentivizing the Reasoning Chain for Video Segmentation with Reinforcement Learning

Intermediate

Yifan Li, Yingda Yin et al.Dec 2arXiv

ReVSeg teaches an AI to segment objects in videos by thinking step-by-step instead of guessing everything at once.

#Reasoning Video Object Segmentation#Vision-Language Models#Temporal Grounding

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PaCo-RL: Advancing Reinforcement Learning for Consistent Image Generation with Pairwise Reward Modeling

Intermediate

Bowen Ping, Chengyou Jia et al.Dec 2arXiv

This paper teaches image models to keep things consistent across multiple pictures—like the same character, art style, and story logic—using reinforcement learning (RL).

#consistent image generation#pairwise reward modeling#reinforcement learning

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