Fine-tuning and adaptation

LoRA, PEFT, instruction tuning and domain adaptation — adapting a pretrained model without paying to train one.

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arXiv Computation and Language

Sep 30

CypherTurn: A Multi-Turn Benchmark for Conversational Text-to-Cypher Evaluation and the Autonomy Divergence

arXiv:2609.36987v1 Announce Type: new Abstract: Graph databases are increasingly queried through natural language, yet every existing benchmark evaluates isolated single-turn queries rather than the...

By Yuzhe Zhang, Weijie Zhu, Haolin Yang, Ziyun Zhang, Xianwei Xue, Mengke Chen, Qiutong Pan, Huaqian Cai

agents fine-tuning benchmarks

arXiv Computation and Language

Sep 30

Who Warmed the Archives? LLMs Overestimate Historical Warmth

arXiv:2609.37499v1 Announce Type: new Abstract: Historical archives are an under-used source for extending the instrumental climate record backward in time, and LLMs offer a way to extract the indice...

By Claudiu Creanga, Liviu P. Dinu

llms fine-tuning benchmarks safety

arXiv Computation and Language

Sep 30

Pruning for Efficiency, Paying in Fairness: Demographic Disparities in Pruned Speech-LLMs

arXiv:2609.38106v1 Announce Type: cross Abstract: Speech-LLMs are expensive to run, making compression important for real-world deployment. However, compressed models are usually selected using aggre...

By Ganesh Pavan Kartikeya Bharadwaj Kolluri, Michael Kampouridis, Ravi Shekhar

llms fine-tuning efficiency multimodal safety

arXiv Computation and Language

Sep 30

POET: Preference Optimization for Enhanced Text-to-Image Generation

arXiv:2510.12041v3 Announce Type: replace Abstract: Recent advances in text-to-image (T2I) generation have achieved impressive results, yet existing models often struggle with simple or underspecifie...

By Ruibo Chen, Jiacheng Pan, Heng Huang, Zhenheng Yang

llms diffusion reinforcement-learning fine-tuning multimodal benchmarks safety

arXiv Computation and Language

Sep 30

IESR:Efficient MCTS-Based Modular Reasoning for Text-to-SQL with Large Language Models

arXiv:2602.05385v2 Announce Type: replace Abstract: Text-to-SQL is a key natural language processing task that maps natural language questions to SQL queries, enabling intuitive interaction with web-...

By Tao Liu, Jiafan Lu, Bohan Yu, Pengcheng Wu, Liu Haixin, Guoyu Xu, Li Xiangheng, Lixiao Li, Jiaming Hou, Zhao Shijun, Xinglin Lyu, Kunli Zhang, Yuxiang Jia, Hongyin Zan

llms nlp fine-tuning benchmarks data-engineering

arXiv Machine Learning

Sep 30

Learning Social Navigation from Internet Videos in the Policy State Space

arXiv:2609.37476v1 Announce Type: cross Abstract: Training robust social-navigation policies requires simulators with diverse scene layouts, terrain, and human motion, but constructing such environme...

By Jiaming Wang, Duc Thang Nguyen, Jizhuo Chen, Volodymyr Shcherbyna, Diwen Liu, Zhengcheng Shen, Harold Soh

robotics fine-tuning benchmarks

arXiv Computation and Language

Sep 30

MoEGen: Mixture-of-Experts for Instance-Adaptive LoRA Generation

arXiv:2608.03275v2 Announce Type: replace Abstract: Parameter-efficient fine-tuning (PEFT) enables efficient adaptation of large language models, but existing MoE-based PEFT methods typically improve...

By Yiming Zeng, Lei Lu, Zexin Li, Zhuochun Li, Dehai Min, Shuoqiu Li, Shuyi Liao, Xidong Wu, Zeyu Zhang, Minmei Wang, Yu Zhao, Tingting Yu, Shangqian Gao

llms fine-tuning benchmarks

arXiv Computation and Language

Sep 30

VectraYX-Vision-1B: A Sub-2B Spanish/LATAM Cybersecurity Vision-Language Model, and What Limits Its Visual Grounding

arXiv:2608.08477v5 Announce Type: replace Abstract: We build VectraYX-Vision-1B, a sub-2B Spanish/LATAM cybersecurity vision-language model for offline use, and measure what limits its visual groundi...

By Juan S. Santillana

llms fine-tuning multimodal benchmarks

arXiv Computation and Language

Sep 30

Bootstrapping Audiovisual Speech Recognition in Zero-AV-Resource Scenarios

arXiv:2603.08249v2 Announce Type: replace-cross Abstract: Audiovisual speech recognition (AVSR) combines acoustic and visual cues to improve transcription robustness under challenging conditions but...

By Pol Buitrago, Javier Hernando

fine-tuning multimodal benchmarks

arXiv Computation and Language

Sep 30

HPRO: Hierarchical Progressive Reward Optimization via Preference Extraction for Emotional Text-to-Speech

arXiv:2606.28249v2 Announce Type: replace-cross Abstract: Recently, Large Language Model (LLM)-based Text-to-Speech (TTS) models have achieved remarkable naturalness. However, the standard Supervised...

By Sihang Nie, Xiaofen Xing, Rui Xing, Haoming Li, Ruitong Xiao, Jingyuan Xing, Baiji Liu, Xiangmin Xu

llms diffusion reinforcement-learning fine-tuning multimodal

arXiv Computer Vision

Sep 30

LeRF: Learning Reference Coordinate Frames for Perspective Taking Reasoning

arXiv:2609.36219v1 Announce Type: new Abstract: Perspective taking is a fundamental component of spatial intelligence, requiring models interpret spatial relations from a specified viewpoint, such as...

By Bang Xiao, Wenqi Jia, Ozgur Kara, Tiancheng Shen, Yibo Yang, Bolin Lai, Junho Kim, James Matthew Rehg

llms reinforcement-learning fine-tuning multimodal benchmarks

arXiv Computer Vision

Sep 30

CrossTimeEdit: A Decade-Spanning Cross-View Dataset and Reward-Guided Editing for Historical Street-View Generation

arXiv:2609.36616v1 Announce Type: new Abstract: Historical street-view imagery records urban evolution, but uneven coverage leaves substantial gaps in historical records. Generating plausible past ap...

By Hanwen Lu, Jun He, Mingjia Yang, Hao Wei, Jinhao Huang, Yi Lin, Xiang Zhang

reinforcement-learning fine-tuning safety

arXiv Computer Vision

Sep 30

OCA: ODE-Driven Cross-Attention for Image-to-Point-Cloud Registration

arXiv:2609.36644v1 Announce Type: new Abstract: Cross-attention is a crucial component in learning-based image-to-point-cloud (I2P) registration. Although existing cross-attention mechanisms have ach...

By Pei An, Jiaqi Yang, Yulong Wang, Siwen Quan, Liangliang Nan

fine-tuning benchmarks

arXiv Computer Vision

Sep 30

Learning via Self-Consistency for Diffusion-based Video Reasoning

arXiv:2609.36826v1 Announce Type: new Abstract: Video generation models have demonstrated emerging zero-shot capabilities for visual reasoning, perception, and other vision tasks. However, diffusion-...

By Zhenghao Ni, Weimin Qiu, Meng Tang

llms diffusion computer-vision fine-tuning efficiency

arXiv Computer Vision

Sep 30

Why MLLMs Struggle to Count: Overcoming Individuation and Aggregation Bottlenecks with ConvStack

arXiv:2609.37096v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) consistently struggle with fine-grained visual counting, yet the underlying causes remain poorly understood. I...

By Liwei Che, Yihao Quan, Sen Fang, Hongyi Wang, Ranjay Krishna, Ruixiang Tang, Vladimir Pavlovic

llms fine-tuning multimodal benchmarks

arXiv Computer Vision

Sep 30

SAM Meets VLM: Parameter-Decoupled Full-Parameter Training for Unified Medical Reasoning and Segmentation

arXiv:2609.37283v1 Announce Type: new Abstract: Medical multimodal large language models (MLLMs) are increasingly expected not only to answer clinical questions, but also to localize the visual evide...

By Xuyang Cao, Enyou Liu, Jun Zhao, Zhuoyun Liu, Jintao Fei, Leo

llms computer-vision fine-tuning multimodal benchmarks safety

arXiv Computer Vision

Sep 30

GeoSET: Generalist Foundation Model for SAR-to-EO Image Translation

arXiv:2609.37496v1 Announce Type: new Abstract: Paired synthetic aperture radar (SAR) and electro-optical (EO) imagery is increasingly available across sensors, resolutions, and geographic regions. Y...

By Jeonghyeok Do, Munchurl Kim

fine-tuning benchmarks

arXiv Computer Vision

Sep 30

Exemplar2VQA: A Scalable Exemplar-Driven Visual Question Answering Generation Framework via Multi-Agent Coding

arXiv:2609.37655v1 Announce Type: new Abstract: Advancing spatial intelligence in Multimodal Large Language Models (MLLMs) is bottlenecked by the scarcity of complex, scalable 3D question-answer (QA)...

By Jiayu Ying, Qijian Tian, Ruijie Xu, Xinnan Zhu, Daoguo Dong, Jiachen Xu, Xin Tan

llms agents nlp robotics fine-tuning multimodal benchmarks

arXiv Computer Vision

Sep 30

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

arXiv:2609.38008v1 Announce Type: new Abstract: Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical us...

By Tongbo Chen, Junbo Niu, Zhengxi Lu, Niu Lian, Fei Tang, Yuchen Yan, Yike Hong, Yong Du, Yizhou Liu, Bofan Chen, Yongliang Shen

agents reinforcement-learning fine-tuning

arXiv Computer Vision

Sep 30

When to Adapt: Multi-Signal Domain Shift Detection for Efficient Training-Free Adaptation in Open-Vocabulary Segmentation

arXiv:2609.37602v1 Announce Type: cross Abstract: Robust and reliable perception is essential for autonomous robots operating in real-world environments, particularly in long-term missions where envi...

By Michele Antonazzi, Alejandra C. Hernandez, Jos\'e Araujo, Olov Andersson, Patric Jensfelt

agents computer-vision robotics fine-tuning benchmarks

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