Isolater - Feed

Ax Minsik Oh, Jiwei Li, Guoyin Wang 4/14/2026

Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings

Proposes contrastive learning method for dialogue sentence embeddings using token-level template annotations instead of utterance-level labels.

Ax Sameera Horawalavithana, Sai Munikoti, Ian Stewart, Henry Kvinge, Karl Pazdernik 4/14/2026

SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions

SciTune framework aligns LLMs with scientific domain knowledge through instruction fine-tuning on multimodal scientific publication data.

Ax Lai Wei, Xiaozhe Li, Zihao Jiang, Weiran Huang, Lichao Sun 4/14/2026

MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets

MM-LIMA demonstrates multimodal LLM fine-tuning achieves strong results with only 200 high-quality instruction examples, reducing data requirements.

Ax Hao Li, Xiao-Hu Zhou, Shu-Hai Li, Mei-Jiang Gui, Xiao-Liang Xie, Shi-Qi Liu, Shuang-Yi Wang, Zhen-Qiu Feng, Zeng-Guang Hou 4/14/2026

CROP: Conservative Reward for Model-based Offline Policy Optimization

Proposes CROP, a model-based offline reinforcement learning method addressing distribution shift through conservative reward estimation.

Ax Hengran Zhang, Keping Bi, Jiafeng Guo, Xueqi Cheng 4/14/2026

An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs

Framework using LLMs with philosophical relevance concepts to improve utility-based result ranking in retrieval-augmented generation systems.

Ax Lionel Z. Wang, Ka Chung Ng, Yiming Ma, Wenqi Fan 4/14/2026

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models

MegaFake dataset of LLM-generated fake news for studying mechanisms of misinformation generation and detection methods.

Ax Avinash Maurya, Jie Ye, M. Mustafa Rafique, Franck Cappello, Bogdan Nicolae 4/14/2026

Deep Optimizer States: Towards Scalable Training of Transformer Models Using Interleaved Offloading

Deep Optimizer States method enables scalable training of transformer models using interleaved offloading to overcome memory constraints.

Ax Qingyang Mao, Qi Liu, Zhi Li, Mingyue Cheng, Zheng Zhang, Rui Li 4/14/2026

PoTable: Towards Systematic Thinking via Plan-then-Execute Stage Reasoning on Tables

PoTable framework improves table reasoning in LLMs using plan-then-execute reasoning stages for systematic thinking.

Ax Charlie F. Ruan, Yucheng Qin, Akaash R. Parthasarathy, Xun Zhou, Ruihang Lai, Hongyi Jin, Yixin Dong, Bohan Hou, Meng-Shiun Yu, Yiyan Zhai, Sudeep Agarwal, Hangrui Cao, Siyuan Feng, Tianqi Chen 4/14/2026

WebLLM: A High-Performance In-Browser LLM Inference Engine

WebLLM inference engine enabling high-performance LLM execution directly in web browsers for on-device deployment without server GPUs.

Ax Ting Zhou, Daoyuan Chen, Qirui Jiao, Bolin Ding, Yaliang Li, Ying Shen 4/14/2026

HumanVBench: Probing Human-Centric Video Understanding in MLLMs with Automatically Synthesized Benchmarks

HumanVBench benchmark for evaluating human-centric video understanding in multimodal large language models with 16 fine-grained tasks.

Ax Stephane Hatgis-Kessell, W. Bradley Knox, Serena Booth, Peter Stone 4/14/2026

Influencing Humans to Conform to Preference Models for RLHF

Three human studies examining whether humans can be influenced to conform to preference models used in RLHF algorithms for LLMs.

Ax Fausto Mauricio Lagos Suarez, Akshit Saradagi, Vidya Sumathy, Shruti Kotpaliwar, George Nikolakopoulos 4/14/2026

Curriculum-based Sample Efficient Reinforcement Learning for Robust Stabilization of a Quadrotor

Novel curriculum learning approach for sample-efficient reinforcement learning applied to quadrotor stabilization control.

Ax Wanli Ma, Oktay Karakus, Paul L. Rosin 4/14/2026

Integrating Semi-Supervised and Active Learning for Semantic Segmentation

Combines semi-supervised and active learning for semantic segmentation to reduce manual annotation costs and improve model performance.

Ax Jun Zhuang, Chaowen Guan 4/14/2026

Large Language Models Can Help Mitigate Barren Plateaus in Quantum Neural Networks

Proposes using LLMs to help mitigate barren plateaus in quantum neural network training through adaptive parameter initialization.

Ax Siqi Fan, Xiusheng Huang, Yiqun Yao, Xuezhi Fang, Kang Liu, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang 4/14/2026

If an LLM Were a Character, Would It Know Its Own Story? Evaluating Lifelong Learning in LLMs

Study evaluating emergent lifelong learning behaviors in LLMs during multi-turn interactions, proposing new evaluation benchmarks for character-like consistency.

Ax Lei Jiang, Chunzhao Xie, Tongxuan Liu, Yuting Zeng, jinrong Guo, Yunheng Shen, Weizhe Huang, Jing Li, Xiaohua Xu 4/14/2026

TARAC: Mitigating Hallucination in LVLMs via Temporal Attention Real-time Accumulative Connection

TARAC method addresses hallucinations in vision-language models by improving temporal attention mechanisms during generation without extensive retraining.

Ax Tahniat Khan, Soroor Motie, Sedef Akinli Kocak, Shaina Raza 4/14/2026

Optimizing Large Language Models: Metrics, Energy Efficiency, and Case Study Insights

Research on energy-efficient optimization techniques for LLM deployment, including quantization and local inference strategies to reduce carbon emissions.

Ax Yixuan Even Xu, Yash Savani, Fei Fang, J. Zico Kolter 4/14/2026

Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning

PODS decouples rollout generation from policy updates in LLM RL, addressing compute asymmetry through down-sampling.

Ax Md Abtahi Majeed Chowdhury, Md Rifat Ur Rahman, Akil Ahmad Taki 4/14/2026

LOOPE: Learnable Optimal Patch Order in Positional Embeddings for Vision Transformers

LOOPE method learns optimal patch ordering in Vision Transformer positional embeddings for improved spatial information encoding.

Ax Kusha Sareen, Morgane M Moss, Alessandro Sordoni, Rishabh Agarwal, Arian Hosseini 4/14/2026

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers

RL^V framework unifies LLM reasoners with verifiers using value functions for improved test-time compute scaling during reasoning.

Ax Tobias Jan Wieczorek, Nathalie Daun, Mohammad Emtiyaz Khan, Marcus Rohrbach 4/14/2026

Variational Visual Question Answering for Uncertainty-Aware Selective Prediction

Bayesian approach for Vision Language Models to reduce hallucinations and overconfidence in VQA through selective prediction.

Ax Tunyu Zhang, Haizhou Shi, Yibin Wang, Hengyi Wang, Xiaoxiao He, Zhuowei Li, Haoxian Chen, Ligong Han, Kai Xu, Huan Zhang, Dimitris Metaxas, Hao Wang 4/14/2026

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning

TokUR enables LLMs to self-assess uncertainty at token-level for improved reasoning and response reliability in multi-step tasks.

Ax Haoning Wu, Xiao Huang, Yaohui Chen, Ya Zhang, Yanfeng Wang, Weidi Xie 4/14/2026

SpatialScore: Towards Comprehensive Evaluation for Spatial Intelligence

SpatialScore: comprehensive benchmark for evaluating spatial intelligence of multimodal LLMs with data-driven and agent-based assessment approaches.

Ax Chengqi Duan, Rongyao Fang, Yuqing Wang, Kun Wang, Linjiang Huang, Xingyu Zeng, Hongsheng Li, Xihui Liu 4/14/2026

GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning

GoT-R1: reinforcement learning framework enhancing multimodal LLM reasoning for complex visual generation with precise spatial relationships and attributes.

Ax Fanjin Meng, Jingtao Ding, Jiahui Gong, Chen Yang, Hong Chen, Zuojian Wang, Haisheng Lu, Yong Li 4/14/2026

Tuning Language Models for Robust Prediction of Diverse User Behaviors

Fine-tuning approach for LLMs to predict diverse user behaviors, addressing overfitting to frequent behaviors while capturing long-tailed behavior distribution.

Ax Taiye Chen, Xun Hu, Zihan Ding, Chi Jin 4/14/2026

Learning World Models for Interactive Video Generation

World models for interactive video generation with action conditioning and autoregressive decoding to support planning and future prediction.

Ax Yongjie Fu, Ruijian Zha, Pei Tian, Xuan Di 4/14/2026

LLM-based Realistic Safety-Critical Driving Video Generation

Framework using LLMs for few-shot code generation to create safety-critical driving scenarios in CARLA simulator for autonomous driving evaluation.

Ax Xu Yang, Chenhui Lin, Licheng Sha, Liping Yang, Shuzhou Wu, Xichen Tian, Haotian Liu, Wenchuan Wu 4/14/2026

Large Language Model as An Operator: An Experience-Driven Solution for Distribution Network Voltage Control

LLM-based autonomous agent for power system voltage control, using experience-driven learning to generate dispatch strategies in distribution networks.

Ax Kailai Yang, Xiao Liu, Lei Ji, Hao Li, Xiao Liang, Zhiwei Liu, Yeyun Gong, Peng Cheng, Mao Yang 4/14/2026

Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training

Data Mixing Agent: LLM-based method to automatically re-weight training data domains during continual pre-training, preventing catastrophic forgetting.

Ax Maciej K. Wozniak, Lianhang Liu, Yixi Cai, Patric Jensfelt 4/14/2026

PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving

PRIX: efficient end-to-end autonomous driving model planning from raw camera pixels without LiDAR, reducing model size and computational requirements.

Ax Haris Khan, Sadia Asif, Shumaila Asif, Muhammad Zeeshan Karamat, Rajesh Upadhayaya 4/14/2026

Modular Delta Merging with Orthogonal Constraints: A Scalable Framework for Continual and Reversible Model Composition

MDM-OC: framework for scalable, reversible model composition enabling continual learning without task interference or catastrophic forgetting.

Ax Soumyadeep Dhar, Kei Sen Fong, Mehul Motani 4/14/2026

Teaching the Teacher: The Role of Teacher-Student Smoothness Alignment in Genetic Programming-based Symbolic Distillation

Genetic programming approach for symbolic distillation of neural networks, using teacher-student smoothness alignment to improve explainable AI model accuracy.

Ax Kisu Yang, Yoonna Jang, Hwanseok Jang, Kenneth Choi, Isabelle Augenstein, Heuiseok Lim 4/14/2026

Reliable Evaluation Protocol for Low-Precision Retrieval

Protocol for reliable evaluation of low-precision retrieval systems, addressing spurious ties and variability in relevance scoring with reduced numerical precision.

Ax Abolfazl Ansari, Delvin Ce Zhang, Nafis Irtiza Tripto, Dongwon Lee 4/14/2026

Echoes of Automation: The Increasing Use of LLMs in Newsmaking

Analysis of LLM use in newsmaking across 40,000+ articles using AI-text detectors, showing increased GenAI adoption in local and college media.

Ax Wenhong Zhu, Ruobing Xie, Rui Wang, Xingwu Sun, Di Wang, Pengfei Liu 4/14/2026

Proximal Supervised Fine-Tuning

Proximal SFT: supervised fine-tuning method using trust-region constraints to prevent capability deterioration when adapting foundation models to new tasks.

Ax Nolan Platt, Pragyansmita Nayak 4/14/2026

Multi-Model Synthetic Training for Mission-Critical Small Language Models

LLM-based synthetic training reduces maritime domain model costs 261x by using LLMs as teachers for small language model training.

Ax Amin Karimi Monsefi, Nikhil Bhendawade, Manuel Rafael Ciosici, Dominic Culver, Yizhe Zhang, Irina Belousova 4/14/2026

FS-DFM: Fast and Accurate Long Text Generation with Few-Step Diffusion Language Models

FS-DFM enables fast long text generation using few-step diffusion language models with parallel position generation.

Ax Junyu Guo, Shangding Gu, Ming Jin, Costas Spanos, Javad Lavaei 4/14/2026

StyleBench: Evaluating thinking styles in Large Language Models

StyleBench evaluates trade-offs between structured reasoning styles and efficiency/robustness in LLM inference.

Ax Fang Wu, Aaron Tu, Weihao Xuan, Heli Qi, Xu Huang, Qingcheng Zeng, Shayan Talaei, Yijia Xiao, Peng Xia, Xiangru Tang, Yuchen Zhuang, Bing Hu, Hanqun Cao, Wenqi Shi, Rui Yang, Nan Liu, Huaxiu Yao, Ge Liu, Li Erran Li, Amin Saberi, Naoto Yokoya, Jure Leskovec, Yejin Choi 4/14/2026