- Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models
Wenxuan Huang, Bohan Jia, Zijie Zhai, Shaosheng Cao, Zheyu Ye · Mar 9, 2025 · Citations: 0
- Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference
Marta Adamska, Daria Smirnova, Hamid Nasiri, Zhengxin Yu, Peter Garraghan · Mar 9, 2025 · Citations: 0
Web Browsing
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models
Yuchen Yan, Yongliang Shen, Yang Liu, Jin Jiang, Mengdi Zhang · Mar 9, 2025 · Citations: 0
Experiments across multiple model architectures demonstrate that our approach reduces computational costs while improving performance, with Qwen2.5-Math-7B showing 3-11% improvements across MATH500, AIME24, and GPQA_diamond benchmarks.
- Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke · Mar 7, 2025 · Citations: 0
When optimized on the BBQ dataset, our individually tuned steering vectors achieve average improvements of 12.8% on BBQ, 8.3% on CLEAR-Bias, and 1% on StereoSet, and show improvements over prompting and Self-Debias in all cases, and…
- Frequency Autoregressive Image Generation with Continuous Tokens
Hu Yu, Hao Luo, Hangjie Yuan, Yu Rong, Jie Huang · Mar 7, 2025 · Citations: 0
However, due to the huge modality gap, image autoregressive models may require a systematic reevaluation from two perspectives: tokenizer format and regression direction.
- No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding
Michael Krumdick, Charles Lovering, Varshini Reddy, Seth Ebner, Chris Tanner · Mar 7, 2025 · Citations: 0
Pairwise Preference
To address this gap, we introduce the Business and Finance Fundamentals Benchmark (BFF-Bench), a dataset of 160 challenging questions and long-form responses authored by financial professionals.
- Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems
Jooyoung Lee, Xiaochen Zhu, Georgi Karadzhov, Tom Stafford, Andreas Vlachos · Mar 6, 2025 · Citations: 0
The proliferation of generative models has presented significant challenges in distinguishing authentic human-authored content from deepfake content.
- VQEL: Enabling Self-Play in Emergent Language Games via Agent-Internal Vector Quantization
Mohammad Mahdi Samiei Paqaleh, Mehdi Jamalkhah, Mahdieh Soleymani Baghshah · Mar 6, 2025 · Citations: 0
Emergent Language (EL) focuses on the emergence of communication among artificial agents.
- Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation
Yu-Seung Roh, Joo-Young Kim, Jin-Duk Park, Won-Yong Shin · Mar 6, 2025 · Citations: 0
- Semantic Parallelism: Redefining Efficient MoE Inference via Model-Data Co-Scheduling
Yan Li, Zhenyu Zhang, Zhengang Wang, Pengfei Chen, Pengfei Zheng · Mar 6, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
Emmy Liu, Amanda Bertsch, Lintang Sutawika, Lindia Tjuatja, Patrick Fernandes · Mar 5, 2025 · Citations: 0
- LINGOLY-TOO: Disentangling Reasoning from Knowledge with Templatised Orthographic Obfuscation
Jude Khouja, Lingyi Yang, Karolina Korgul, Simeon Hellsten, Vlad A. Neacsu · Mar 4, 2025 · Citations: 0
We introduce LINGOLY-TOO, a challenging reasoning benchmark of 1,203 questions and a total of 6,995 sub-questions that counters these shortcuts by applying expert-designed obfuscations to Linguistics Olympiad problems.
- Wikipedia in the Era of LLMs: Evolution and Risks
Siming Huang, Yuliang Xu, Mingmeng Geng, Yao Wan, Dongping Chen · Mar 4, 2025 · Citations: 0
If the machine translation benchmark based on Wikipedia is influenced by LLMs, the scores of the models may become inflated, and the comparative results among models could shift.
- Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
David Bani-Harouni, Chantal Pellegrini, Paul Stangel, Ege Özsoy, Kamilia Zaripova · Mar 4, 2025 · Citations: 0
- HoT: Highlighted Chain of Thought for Referencing Supporting Facts from Inputs
Tin Nguyen, Logan Bolton, Mohammad Reza Taesiri, Trung Bui, Anh Totti Nguyen · Mar 3, 2025 · Citations: 0
A response mixed of factual and non-factual statements poses a challenge for humans to verify and accurately base their decisions on.
- $\texttt{SEM-CTRL}$: Semantically Controlled Decoding
Mohammad Albinhassan, Pranava Madhyastha, Alessandra Russo · Mar 3, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- LLM-Advisor: An LLM Benchmark for Cost-efficient Path Planning across Multiple Terrains
Ling Xiao, Toshihiko Yamasaki · Mar 3, 2025 · Citations: 0
Web Browsing
We further introduce two datasets, MultiTerraPath and RUGD_v2, for systematic evaluation of cost-efficient path planning.
- Steering Dialogue Dynamics for Robustness against Multi-turn Jailbreaking Attacks
Hanjiang Hu, Alexander Robey, Changliu Liu · Feb 28, 2025 · Citations: 0
Red Team
To address this challenge, we propose a safety steering framework grounded in safe control theory, ensuring invariant safety in multi-turn dialogues.
- Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models
Ruta Binkyte, Ivaxi Sheth, Zhijing Jin, Mohammad Havaei, Bernhard Schölkopf · Feb 28, 2025 · Citations: 0
- Prediction of Item Difficulty for Reading Comprehension Items by Creation of Annotated Item Repository
Radhika Kapoor, Sang T. Truong, Nick Haber, Maria Araceli Ruiz-Primo, Benjamin W. Domingue · Feb 28, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- HaLoRA: Hardware-aware Low-Rank Adaptation for Large Language Models Based on Hybrid Compute-in-Memory Architecture
Taiqiang Wu, Chenchen Ding, Wenyong Zhou, Yuxin Cheng, Xincheng Feng · Feb 27, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- Stay Focused: Problem Drift in Multi-Agent Debate
Jonas Becker, Lars Benedikt Kaesberg, Andreas Stephan, Jan Philip Wahle, Terry Ruas · Feb 26, 2025 · Citations: 0
Multi Agent
Multi-agent debate - multiple instances of large language models discussing problems in turn-based interaction - has shown promise for solving knowledge and reasoning tasks.
- The Mighty ToRR: A Benchmark for Table Reasoning and Robustness
Shir Ashury-Tahan, Yifan Mai, Rajmohan C, Ariel Gera, Yotam Perlitz · Feb 26, 2025 · Citations: 0
To address this gap, we create ToRR, a benchmark for Table Reasoning and Robustness, measuring model performance and robustness on table-related tasks.
- Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning
Hongyi Cai, Jie Li, Mohammad Mahdinur Rahman, Wenzhen Dong · Feb 26, 2025 · Citations: 0
Experimental evaluation demonstrates that models fine-tuned on LCG-filtered subsets of 6K samples achieve superior performance compared to existing methods, with substantial improvements on MT-bench and consistent gains across comprehensive…
- Transforming the Voice of the Customer: Large Language Models for Identifying Customer Needs
Artem Timoshenko, Chengfeng Mao, John R. Hauser · Feb 25, 2025 · Citations: 0
While current practice uses machine learning to screen content, the critical final step of precisely formulating CNs relies on expert human judgment.
- Compressing Language Models for Specialized Domains
Miles Williams, George Chrysostomou, Vitor Jeronymo, Nikolaos Aletras · Feb 25, 2025 · Citations: 0
Compression techniques such as pruning and quantization offer a practical path towards efficient LM deployment, exemplified by their ability to preserve performance on general-purpose benchmarks.
- Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization
Ru Wang, Wei Huang, Selena Song, Haoyu Zhang, Qian Niu · Feb 25, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- PII-Bench: Evaluating Query-Aware Privacy Protection Systems
Hao Shen, Zhouhong Gu, Haokai Hong, Weili Han · Feb 25, 2025 · Citations: 0
To address this challenge, we propose a query-unrelated PII masking strategy and introduce PII-Bench, the first comprehensive evaluation framework for assessing privacy protection systems.
- Connecting Voices: LoReSpeech as a Low-Resource Speech Parallel Corpus
Samy Ouzerrout · Feb 25, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- Can Multimodal LLMs Perform Time Series Anomaly Detection?
Xiongxiao Xu, Haoran Wang, Yueqing Liang, Philip S. Yu, Yue Zhao · Feb 25, 2025 · Citations: 0
Multi Agent
One natural way for humans to detect time series anomalies is through visualization and textual description.
- Renormalization-Inspired Effective Field Neural Networks for Scalable Modeling of Classical and Quantum Many-Body Systems
Xi Liu, Yujun Zhao, Chun Yu Wan, Yang Zhang, Junwei Liu · Feb 24, 2025 · Citations: 0
- LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification
Penghui Yang, Cunxiao Du, Fengzhuo Zhang, Haonan Wang, Tianyu Pang · Feb 24, 2025 · Citations: 0
As Large Language Models (LLMs) can now process extremely long contexts, efficient inference over these extended inputs has become increasingly important, especially for emerging applications like LLM agents that highly depend on this…
- Bridging Gaps in Natural Language Processing for Yorùbá: A Systematic Review of a Decade of Progress and Prospects
Toheeb Aduramomi Jimoh, Tabea De Wille, Nikola S. Nikolov · Feb 24, 2025 · Citations: 0
Natural Language Processing (NLP) is becoming a dominant subset of artificial intelligence as the need to help machines understand human language looks indispensable.
- HIPPO: Enhancing the Table Understanding Capability of LLMs through Hybrid-Modal Preference Optimization
Haolan Wang, Zhenghao Liu, Xinze Li, Xiaocui Yang, Yu Gu · Feb 24, 2025 · Citations: 0
Pairwise Preference
To better capture structural semantics from the tabular data, this paper introduces the HybrId-modal Preference oPtimizatiOn (HIPPO) model, which represents tables using both text and image, optimizing MLLMs by learning more comprehensive…
- Unveiling Downstream Performance Scaling of LLMs: A Clustering-Based Perspective
Chengyin Xu, Kaiyuan Chen, Xiao Li, Ke Shen, Chenggang Li · Feb 24, 2025 · Citations: 0
Predictable subset performance acts as an intermediate predictor for the full evaluation set.
- From Euler to AI: Unifying Formulas for Mathematical Constants
Tomer Raz, Michael Shalyt, Elyasheev Leibtag, Rotem Kalisch, Shachar Weinbaum · Feb 24, 2025 · Citations: 0
- Distributional Vision-Language Alignment by Cauchy-Schwarz Divergence
Wenzhe Yin, Zehao Xiao, Pan Zhou, Shujian Yu, Jiayi Shen · Feb 24, 2025 · Citations: 0
Pairwise Preference
Vision-language alignment is crucial for various downstream tasks such as cross-modal generation and retrieval.
- Make LoRA Great Again: Boosting LoRA with Adaptive Singular Values and Mixture-of-Experts Optimization Alignment
Chenghao Fan, Zhenyi Lu, Sichen Liu, Chengfeng Gu, Xiaoye Qu · Feb 24, 2025 · Citations: 0
Abstract shows limited direct human-feedback or evaluation-protocol detail; use as adjacent methodological context.
- Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions
Joseph Suh, Erfan Jahanparast, Suhong Moon, Minwoo Kang, Serina Chang · Feb 24, 2025 · Citations: 0
Prior methods steer LLMs via descriptions of subpopulations as LLMs' input prompt, yet such prompt engineering approaches have struggled to faithfully predict the distribution of survey responses from human subjects.