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Kiwi-Edit: Versatile Video Editing via Instruction and Reference Guidance

Intermediate

Yiqi Lin, Guoqiang Liang et al.Mar 2arXiv

Kiwi-Edit is a new video editor that follows your words and also copies looks from a picture you give it.

#reference-guided video editing#instruction-based editing#multimodal large language model

Recursive Think-Answer Process for LLMs and VLMs

Intermediate

Byung-Kwan Lee, Youngchae Chee et al.Mar 2arXiv

This paper teaches AI models to judge how sure they are about an answer and to think again if they are not sure.

#Recursive Think–Answer#Confidence-guided reasoning#Reinforcement learning for LLMs

WorldStereo: Bridging Camera-Guided Video Generation and Scene Reconstruction via 3D Geometric Memories

Intermediate

Yisu Zhang, Chenjie Cao et al.Mar 2arXiv

WorldStereo is a method that turns a single photo (or a panorama) into a short set of camera-guided videos and then reconstructs a consistent 3D scene from them.

#video diffusion models#camera control#3D reconstruction

CharacterFlywheel: Scaling Iterative Improvement of Engaging and Steerable LLMs in Production

Intermediate

Yixin Nie, Lin Guan et al.Mar 2arXiv

CharacterFlywheel is a step‑by‑step loop that steadily improves chatty AI characters by learning from real conversations on Instagram, WhatsApp, and Messenger.

#CharacterFlywheel#large language models#conversational AI

CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification

Intermediate

Jinpeng Chen, Cheng Gong et al.Mar 2arXiv

CoVe is a way to create training conversations for AI agents that use tools, while guaranteeing the conversations are both challenging and correct.

#constraint-guided verification#multi-turn tool use#user simulator

Efficient RLVR Training via Weighted Mutual Information Data Selection

Intermediate

Xinyu Zhou, Boyu Zhu et al.Mar 2arXiv

Reinforcement learning (RL) trains language models by letting them try answers and learn from rewards, but training is slow if we pick the wrong practice questions.

#Reinforcement Learning#RLVR#Data Selection

Agentic Code Reasoning

Intermediate

Shubham Ugare, Satish ChandraMar 2arXiv

The paper teaches AI agents to understand big codebases without running the code by following a strict, step-by-step thinking template called semi-formal reasoning.

#agentic code reasoning#semi-formal reasoning#patch equivalence

FireRed-OCR Technical Report

Intermediate

Hao Wu, Haoran Lou et al.Mar 2arXiv

FireRed-OCR turns a general vision-language model into a careful document reader that follows strict rules, so its outputs are usable in the real world.

#FireRed-OCR#structural hallucination#document parsing

Surgical Post-Training: Cutting Errors, Keeping Knowledge

Intermediate

Wenye Lin, Kai HanMar 2arXiv

The paper introduces SPOT, a training recipe that fixes an AI model’s mistakes with tiny edits while keeping what it already knows well.

#Surgical Post-Training#SPOT#DPO

Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models

Intermediate

Qiyuan Zhang, Yufei Wang et al.Mar 2arXiv

Longer explanations are not always better; the shape of thinking matters.

#Generative Reward Models#Chain-of-Thought#Breadth-CoT

RubricBench: Aligning Model-Generated Rubrics with Human Standards

Intermediate

Qiyuan Zhang, Junyi Zhou et al.Mar 2arXiv

RubricBench is a new benchmark that checks whether AI judges can use clear, checklist-style rules (rubrics) the way humans do.

#RubricBench#rubric-guided evaluation#reward models

LaSER: Internalizing Explicit Reasoning into Latent Space for Dense Retrieval

Intermediate

Jiajie Jin, Yanzhao Zhang et al.Mar 2arXiv

LaSER teaches a fast search model to “think” quietly inside its hidden space, so it gets the benefits of step-by-step reasoning without writing those steps out as text.

#dense retrieval#chain-of-thought#latent reasoning

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