惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

Y
Y Combinator Blog
S
SegmentFault 最新的问题
Engineering at Meta
Engineering at Meta
量子位
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Google DeepMind News
Google DeepMind News
博客园_首页
云风的 BLOG
云风的 BLOG
月光博客
月光博客
I
InfoQ
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
Vercel News
Vercel News
美团技术团队
Microsoft Security Blog
Microsoft Security Blog
P
Proofpoint News Feed
D
Docker
F
Fortinet All Blogs
N
Netflix TechBlog - Medium
博客园 - 叶小钗
Martin Fowler
Martin Fowler
雷峰网
雷峰网
酷 壳 – CoolShell
酷 壳 – CoolShell
J
Java Code Geeks
Microsoft Azure Blog
Microsoft Azure Blog

cs.IR updates on arXiv.org

From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems Impact of large language models on peer review opinions from a fine-grained perspective: Evidence from top conference proceedings in AI Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract CAST: Modeling Semantic-Level Transitions for Complementary-Aware Sequential Recommendation IndiaFinBench: An Evaluation Benchmark for Large Language Model Performance on Indian Financial Regulatory Text Think Before Writing: Feature-Level Multi-Objective Optimization for Generative Citation Visibility RARE: Redundancy-Aware Retrieval Evaluation Framework for High-Similarity Corpora Personalized Benchmarking: Evaluating LLMs by Individual Preferences Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations JFinTEB: Japanese Financial Text Embedding Benchmark UsefulBench: Towards Decision-Useful Information as a Target for Information Retrieval SIMMER: Cross-Modal Food Image--Recipe Retrieval via MLLM-Based Embedding Rethinking the Necessity of Adaptive Retrieval-Augmented Generation through the Lens of Adaptive Listwise Ranking BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels Learning Behaviorally Grounded Item Embeddings via Personalized Temporal Contexts Collaborative Filtering Through Weighted Similarities of User and Item Embeddings IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning Metric-agnostic Learning-to-Rank via Boosting and Rank Approximation GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation Uncertainty-aware Generative Learning Path Recommendation with Cognition-Adaptive Diffusion CPGRec+: A Balance-oriented Framework for Personalized Video Game Recommendations Don't Retrieve, Navigate: Distilling Enterprise Knowledge into Navigable Agent Skills for QA and RAG NewsTorch: A PyTorch-based Toolkit for Learner-oriented News Recommendation Controlling Authority Retrieval: A Missing Retrieval Objective for Authority-Governed Knowledge APEX-MEM: Agentic Semi-Structured Memory with Temporal Reasoning for Long-Term Conversational AI ID and Graph View Contrastive Learning with Multi-View Attention Fusion for Sequential Recommendation Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends Dual-Enhancement Product Bundling: Bridging Interactive Graph and Large Language Model Evaluation of Agents under Simulated AI Marketplace Dynamics
Proceedings of 1st International Workshop on Collaborativ...
Jeremy Pickens, Gene Golovchinsky, Meredith Ringel Morris · 2009-08-05 · via cs.IR updates on arXiv.org

The goal of the workshop is to bring together researchers interested in various aspects of small-team collaborative search to share ideas, to stimulate research in the area, and to increase the visibility of this emerging area. We expect to identify promising directions for further exploration and to establish collaborative links among research groups. The workshop took place on June 20, 2008 in Pittsburgh, Pennsylvania, USA, in conjunction with the JCDL 2008 conference. The workshop was organized around three themes: practices, models, and evaluation. We started with a discussion (still ongoing) about terminology, about how to situate our work in the existing research space. We also wanted to motivate our modeling and design discussions with real-world examples of collaboration. We discussed examples from the healthcare domain, students, faculty members, the military, and businesses such as pharmaceutical companies that conduct research. We discussed several models of collaborative information seeking, including sense-making, communication, and information seeking theory based on Marcia Bates' Berrypicking theory. Finally, presenters described several systems that implement various aspects of collaboration, including using search paths, simulations of user behavior to model system performance, and characterizing properties of groups that lead to more effective collaboration.