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![[2603.05659] When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual Try-On](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.05659: When Rubrics Fail: Error Enumeration as Reward in Reference-Free RL Post-Training for Virtual T...
Abstract page for arXiv paper 2512.16081: Evaluation of Generative Models for Emotional 3D Animation Generation in VR
Abstract page for arXiv paper 2510.16635: MA-SAPO: Multi-Agent Reasoning for Score-Aware Prompt Optimization
CodeHacker is an automated framework designed to generate test cases that identify vulnerabilities in competitive programming solutions, ...
This paper investigates the impact of encoder-side poisoning on text-to-image models, revealing that traditional evaluations of backdoor ...
The paper introduces CAGE, a framework for culturally adaptive red-teaming benchmark generation, addressing the limitations of existing b...
The paper introduces DEEPSYNTH, a benchmark for evaluating large language models on complex tasks requiring deep information synthesis an...
LogicGraph introduces a benchmark for evaluating multi-path logical reasoning in large language models, highlighting their limitations in...
This article introduces Vision-Language Causal Graphs (VLCGs) to enhance causal reasoning in Vision-Language Models (LVLMs), addressing t...
This paper presents a novel evaluation framework for assessing the alignment of language models under realistic pressure, revealing behav...
The paper presents Qwen-BIM, a large language model tailored for BIM-based design, introducing a domain-specific benchmark and dataset th...
POMDPPlanners is an open-source Python package designed for the empirical evaluation of POMDP planning algorithms, integrating advanced f...
This article discusses the limitations of current benchmarks for vision-language model (VLM)-driven embodied agents and introduces Native...
The paper discusses a method for identifying two piecewise linear additive value functions from anonymous preference information, enhanci...
The CausalReasoningBenchmark introduces a new framework for evaluating automated causal inference, distinguishing between identification ...
The paper introduces KairosVL, a novel framework that enhances time series analysis by integrating semantic reasoning, achieving competit...
This study evaluates multilevel determinants of overweight and obesity among U.S. children aged 10-17, comparing statistical and machine ...
Anthropic has announced the discontinuation of its flagship safety pledge, raising concerns about AI safety commitments in the industry.
The article discusses a Pentagon meeting involving Defense Secretary Pete Hegseth, former Uber executive Emil Michael, and private equity...
The Behavior Buddy app, developed by UT San Antonio researchers, offers caregivers of children with autism practical support and behavior...
Concerns over AI spending are causing volatility in Wall Street, as investors question profitability. Major companies like IBM and Master...
India's AI market is witnessing a pivotal shift as tech firms transition from free offerings to monetization strategies, testing user con...
MatX, an AI chip startup founded by ex-Google engineers, has raised $500M in Series B funding to develop processors aimed at outperformin...
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