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 AI

Oct 15

Look Back to Move Forward: Learning to Revisit for Agentic Compositional Image Generation

arXiv:2610.16224v1 Announce Type: cross Abstract: Text-to-image models have made remarkable progress in visual fidelity and instruction following, yet complex compositional generation remains challen...

By Zixu Wang, Xiaoran Zhao, Yahui Liu, Feng-ao Wang, Junhao Xiao, You Shu, Bing Liu, Yiting Liu, Songlei Jian, Zhiliang Tian, Dongsheng Li

agents diffusion reinforcement-learning fine-tuning benchmarks

arXiv AI

Oct 15

A Survey of Flow Matching in Reinforcement Learning

arXiv:2610.16275v1 Announce Type: cross Abstract: Flow Matching (FM) has recently emerged as a principled and efficient generative modeling framework for reinforcement learning (RL), enabling express...

By Nabuat Zaman Nahim, Fairoz Nower Khan, Peizhong Ju

diffusion reinforcement-learning fine-tuning efficiency multimodal safety

arXiv AI

Oct 15

Iterate on an LLM, Serve on an SLM

arXiv:2610.14576v1 Announce Type: new Abstract: As frontier LLMs gain more capabilities, the cost to run them also goes up. At the same time, small language models (SLMs) also gain more capabilities...

By Keegan Wang

llms agents fine-tuning safety

arXiv AI

Oct 15

MoMaTune: Model, Match, Then Tune Language Models for Numerical Records

arXiv:2610.15235v1 Announce Type: new Abstract: Despite remarkable progress in language understanding and generation, decoder language models continue to exhibit striking failures on numerical data....

By Weimin Lyu, Jingfen Zhang, Lingdao Sha, Peng sun, Xiaowei Chen, Vincent Gao, Rui Song

llms rag fine-tuning

arXiv AI

Oct 15

LLM2R: From Large Language Models to 3D Reassemblers

arXiv:2610.18604v1 Announce Type: cross Abstract: 3D part assembly aims to reconstruct a complete shape from a set of unassembled parts by predicting a rigid SE(3) transformation for each part. Becau...

By Zhouhan Zhong, Qiuhong Shen, Xingyi Yang, Jinyi Xu, Xinchao Wang

llms fine-tuning

arXiv AI

Oct 15

LIFT: Likelihood-Based Intervention Faithfulness Training

arXiv:2509.13334v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning improves LLM accuracy on complex tasks, but CoTs are often unfaithful; that is, the model does not rely on the sta...

By Anand Swaroop, Maheep Chaudhary, Kevin Zhu, Sunishchal Dev, Vasu Sharma

llms fine-tuning benchmarks

arXiv Computation and Language

Oct 15

MemDuet: Learning Dual-Process Memory for Long-Context Reasoning

arXiv:2610.19928v1 Announce Type: new Abstract: Reasoning over infinitely long documents is becoming a reality with recurrent memory agents. However, increasing context length exacerbates the trade-o...

By Jiangcheng Song, Haodong Jing, Yulin Mu, Lesong Tao, Jixin Wang, Jin Cui, Tianjing Ren, Runxuan Xie, Yongqiang Ma, Nanning Zheng

llms agents reinforcement-learning fine-tuning benchmarks

arXiv Computer Vision

Oct 15

Selective Prediction Forgetting for Adaptation of Weakly Supervised Localization of Histology Images

arXiv:2603.12468v2 Announce Type: replace Abstract: Under strong cross-domain shifts, weakly supervised object localization (WSOL) models often lose their capacity to discriminate and develop a stron...

By Alexis Guichemerre, Banafsheh Karimian, Soufiane Belharbi, Natacha Gillet, Nicolas Thome, Pourya Shamsolmoali, Mohammadhadi Shateri, Luke McCaffrey, Eric Granger

fine-tuning safety

arXiv Machine Learning

Oct 15

Parameter-Efficient Temporal Domain Generalization

arXiv:2602.11965v2 Announce Type: replace Abstract: Temporal domain generalization (TDG) learns from a sequence of observed domains to predict models for unseen future domains. Existing parameter-dyn...

By Zekun Cai, Xinyuan Song, Yiheng Yao, Xuan Song, Ryosuke Shibasaki, Liang Zhao

fine-tuning benchmarks

arXiv AI

Oct 15

Agentic neural architecture search for clinical prediction from electronic health records: Cross-hospital knowledge transfer and computational efficiency

arXiv:2608.21712v3 Announce Type: replace Abstract: Transformer architectures for clinical prediction from electronic health records (EHRs) often require costly manual tuning and may vary across hosp...

By Deyi Li, Qi Xu, Lingyao Li, Tiansheng Wang, Muxuan Liang, Mei Liu

llms agents fine-tuning

arXiv AI

Oct 15

Discrete Flow Matching for Offline-to-Online Reinforcement Learning

arXiv:2605.12379v2 Announce Type: replace-cross Abstract: Many reinforcement learning (RL) tasks have discrete action spaces, but most generative policy methods based on diffusion and flow matching a...

By Fairoz Nower Khan, Nabuat Zaman Nahim, Peizhong Ju

diffusion reinforcement-learning fine-tuning

arXiv AI

Oct 15

LLM Alignment--Utility Asymmetry under Semantic-Preserving Transformations

arXiv:2609.32717v2 Announce Type: replace-cross Abstract: Large Language Model (LLM) alignment is intended to ensure that models remain helpful and safe, but its stability under input distributional...

By Mohan Li, Chengyu Yu, Francesco Sovrano, Marc Langheinrich, Martin Gjoreski

llms fine-tuning safety

arXiv AI

Oct 15

Training a Compact, Strong, and Realistic Text-to-Speech Model

arXiv:2610.14776v1 Announce Type: cross Abstract: Text-to-speech (TTS) systems are conventionally optimized for intelligibility and speaker similarity. However, neither objective captures the prosodi...

By Runyuan Cai, Yu Lin, Yiming Wang, Xiaodong Zeng

fine-tuning multimodal benchmarks

arXiv AI

Oct 15

Sequent-Prover: Training Agents for Formal, Checkable SMT-based Reasoning

arXiv:2610.15258v1 Announce Type: cross Abstract: We introduce Sequent-Prover, a family of verifier-using language-model agents, and the post-training framework that produces them. Agents reason in a...

By Debargha Ganguly, Weicong Chen, Mohsen Hariri, Vikash Singh, Sreehari Sankar, Shouren Wang, Wang Yang, Biyao Zhang, Chaoda Song, Alexander Nemecek, Kai Ye, Osama Zafar, Erman Ayday, Joe Stubbs, Srinivasan Iyengar, Vipin Chaudhary

agents fine-tuning efficiency benchmarks

arXiv Computer Vision

Oct 15

Improving Category-Aware Active Domain Adaptation via Uncertainty-Guided Region Coverage

arXiv:2610.19803v1 Announce Type: new Abstract: Active domain adaptation researches focus on alleviating the annotation cost, which comprises source data and target data labelling, as well as enhanci...

By My Tra Nguyen Huynh, Viet Cuong Ta

fine-tuning benchmarks

arXiv AI

Oct 15

XAI-Guided Fourier Domain Generalisation for Pure-Simulation Sim-to-Real Deep Reinforcement Learning

arXiv:2610.16478v1 Announce Type: new Abstract: Deep reinforcement learning has shown strong potential for vision-based autonomous driving, but policies trained in simulation often suffer severe perf...

By Wei Yao, Chuyao Wang, Ziwei Wang, Nabil Aouf

agents reinforcement-learning robotics fine-tuning

arXiv AI

Oct 15

G$^2$WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

arXiv:2610.16558v1 Announce Type: new Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies beyo...

By Ke Gui, Chenghao Shi, Ziyue Wang, Longwen Chen, Xieyuanli Chen, Huimin Lu

agents diffusion fine-tuning benchmarks

arXiv AI

Oct 15

WildTrace: Evaluating Training Data Detection in Realistic Large-Scale LLM Post-Training

arXiv:2610.16152v1 Announce Type: cross Abstract: Although post-training significantly enhances model performance, the use of massive undisclosed data raises concerns about benchmark contamination an...

By Hengxiang Zhang, Junxian Liu, Hongxin Wei

llms reinforcement-learning fine-tuning benchmarks

arXiv AI

Oct 15

VisExMEM: Visual Evidence-Based Explainable Multimodal Evaluation Metric

arXiv:2610.16441v1 Announce Type: cross Abstract: Current image-text evaluation often relies on a global score, which gives limited insight into which semantic details are supported by the image. Exp...

By Subhadeep Roy, Christoph Leiter, Steffen Eger

llms fine-tuning multimodal benchmarks

arXiv AI

Oct 15

Cowork-Gym: Synthesizing Interactive Work Environments at Scale

arXiv:2610.17670v1 Announce Type: new Abstract: Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such en...

By Anni Zou, Cheng Chen, Jiaji Deng, Weikang Zhou, Xinji Mai, Yue Wu, Jianing Lin, Lipeng Xie, Lixiong Qin, Qingyue Zhao, Que Shen, Shuchang Tao, Xuchen Pan, Yaliang Li, Yunpeng Zhai, Yushuo Chen, Zhihai Wang, Zhuo Zhang, Zhaoyang Liu, Bolin Ding, Jingren Zhou

agents reinforcement-learning fine-tuning efficiency benchmarks

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