Poster "large language models" Papers
740 papers found • Page 11 of 15
Conference
Triplets Better Than Pairs: Towards Stable and Effective Self-Play Fine-Tuning for LLMs
Yibo Wang, Hai-Long Sun, Guangda Huzhang et al.
Trust, But Verify: A Self-Verification Approach to Reinforcement Learning with Verifiable Rewards
Xiaoyuan Liu, Tian Liang, Zhiwei He et al.
Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection
Herun Wan, Jiaying Wu, Minnan Luo et al.
TSENOR: Highly-Efficient Algorithm for Finding Transposable N:M Sparse Masks
Xiang Meng, Mehdi Makni, Rahul Mazumder
T-SHIRT: Token-Selective Hierarchical Data Selection for Instruction Tuning
Yanjun Fu, Faisal Hamman, Sanghamitra Dutta
TTRL: Test-Time Reinforcement Learning
Yuxin Zuo, Kaiyan Zhang, Li Sheng et al.
Týr-the-Pruner: Structural Pruning LLMs via Global Sparsity Distribution Optimization
Guanchen Li, Yixing Xu, Zeping Li et al.
UGMathBench: A Diverse and Dynamic Benchmark for Undergraduate-Level Mathematical Reasoning with Large Language Models
Xin Xu, Jiaxin ZHANG, Tianhao Chen et al.
Understanding and Enhancing the Transferability of Jailbreaking Attacks
Runqi Lin, Bo Han, Fengwang Li et al.
UniEdit: A Unified Knowledge Editing Benchmark for Large Language Models
Qizhou Chen, Dakan Wang, Taolin Zhang et al.
Universal Cross-Tokenizer Distillation via Approximate Likelihood Matching
Benjamin Minixhofer, Ivan Vulić, Edoardo Maria Ponti
Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
Xiaoyu Wu, Yifei Pang, Terrance Liu et al.
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
Tianci Liu, Ruirui Li, Yunzhe Qi et al.
Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning
Gangwei Jiang, caigao jiang, Zhaoyi Li et al.
Unveiling the Magic of Code Reasoning through Hypothesis Decomposition and Amendment
Yuze Zhao, Tianyun Ji, Wenjun Feng et al.
U-shaped and Inverted-U Scaling behind Emergent Abilities of Large Language Models
Tung-Yu Wu, Melody Lo
Valid Inference with Imperfect Synthetic Data
Yewon Byun, Shantanu Gupta, Zachary Lipton et al.
VALLR: Visual ASR Language Model for Lip Reading
Marshall Thomas, Edward Fish, Richard Bowden
Variational Uncertainty Decomposition for In-Context Learning
I. Shavindra Jayasekera, Jacob Si, Filippo Valdettaro et al.
VERA: Variational Inference Framework for Jailbreaking Large Language Models
Anamika Lochab, Lu Yan, Patrick Pynadath et al.
Video Summarization with Large Language Models
Min Jung Lee, Dayoung Gong, Minsu Cho
ViLLa: Video Reasoning Segmentation with Large Language Model
rongkun Zheng, Lu Qi, Xi Chen et al.
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance et al.
VT-FSL: Bridging Vision and Text with LLMs for Few-Shot Learning
Wenhao Li, Qiangchang Wang, Xianjing Meng et al.
Weak to Strong Generalization for Large Language Models with Multi-capabilities
Yucheng Zhou, Jianbing Shen, Yu Cheng
Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation
Hyungjoo Chae, Namyoung Kim, Kai Ong et al.
What Happens During the Loss Plateau? Understanding Abrupt Learning in Transformers
Pulkit Gopalani, Wei Hu
What Makes Large Language Models Reason in (Multi-Turn) Code Generation?
Kunhao Zheng, Juliette Decugis, Jonas Gehring et al.
What's Producible May Not Be Reachable: Measuring the Steerability of Generative Models
Keyon Vafa, Sarah Bentley, Jon Kleinberg et al.
When Can Model-Free Reinforcement Learning be Enough for Thinking?
Josiah Hanna, Nicholas Corrado
Why Does the Effective Context Length of LLMs Fall Short?
Chenxin An, Jun Zhang, Ming Zhong et al.
Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation
Sungmin Cha, Kyunghyun Cho
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild
Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu et al.
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Haipeng Luo, Qingfeng Sun, Can Xu et al.
WritingBench: A Comprehensive Benchmark for Generative Writing
Yuning Wu, Jiahao Mei, Ming Yan et al.
xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation
Qingchen Yu, Zifan Zheng, Shichao Song et al.
Zero-AVSR: Zero-Shot Audio-Visual Speech Recognition with LLMs by Learning Language-Agnostic Speech Representations
Jeong Hun Yeo, Minsu Kim, Chae Won Kim et al.
Zero-shot Model-based Reinforcement Learning using Large Language Models
Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.
Accelerated Speculative Sampling Based on Tree Monte Carlo
Zhengmian Hu, Heng Huang
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
A Closer Look at the Limitations of Instruction Tuning
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar et al.
Active Preference Learning for Large Language Models
William Muldrew, Peter Hayes, Mingtian Zhang et al.
Adaptive Text Watermark for Large Language Models
Yepeng Liu, Yuheng Bu
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Nicholas Crispino, Kyle Montgomery, Fankun Zeng et al.
Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar et al.
AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training
Ziyu Wan, Xidong Feng, Muning Wen et al.
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.
Assessing Large Language Models on Climate Information
Jannis Bulian, Mike Schäfer, Afra Amini et al.
Asynchronous Large Language Model Enhanced Planner for Autonomous Driving
Yuan Chen, Zi-han Ding, Ziqin Wang et al.
A Tale of Tails: Model Collapse as a Change of Scaling Laws
Elvis Dohmatob, Yunzhen Feng, Pu Yang et al.