data/seed_papers.json

[
  {
    "arxiv_id": "2401.04088",
    "title": "DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence",
    "domain": "aiml",
    "categories": ["cs.CL", "cs.SE", "cs.AI"],
    "summary": "Open-source code LLM matching GPT-4 Turbo on coding benchmarks with MoE architecture."
  },
  {
    "arxiv_id": "2403.05530",
    "title": "GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection",
    "domain": "aiml",
    "categories": ["cs.LG", "cs.CL"],
    "summary": "Reduces memory usage for LLM training via gradient projection, enabling 7B training on consumer GPUs."
  },
  {
    "arxiv_id": "2402.13616",
    "title": "World Model on Million-Length Video and Language with RingAttention",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.CL", "cs.LG"],
    "summary": "Trains world models on million-token video sequences using ring attention for long context."
  },
  {
    "arxiv_id": "2403.03206",
    "title": "The Claude 3 Model Family",
    "domain": "aiml",
    "categories": ["cs.CL", "cs.AI"],
    "summary": "Multimodal LLM family with strong vision capabilities and extended context windows."
  },
  {
    "arxiv_id": "2402.17764",
    "title": "Sora: A Review on Background, Technology, Limitations, and Opportunities",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.AI"],
    "summary": "Analysis of video generation model capabilities, architecture, and limitations."
  },
  {
    "arxiv_id": "2401.02954",
    "title": "MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts",
    "domain": "aiml",
    "categories": ["cs.LG", "cs.CL"],
    "summary": "Combines Mamba state-space model with mixture-of-experts for efficient scaling."
  },
  {
    "arxiv_id": "2403.09611",
    "title": "Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking",
    "domain": "aiml",
    "categories": ["cs.CL", "cs.AI", "cs.LG"],
    "summary": "Self-taught reasoning where LLMs learn to generate internal rationale tokens."
  },
  {
    "arxiv_id": "2402.01032",
    "title": "OLMo: Accelerating the Science of Language Models",
    "domain": "aiml",
    "categories": ["cs.CL", "cs.AI"],
    "summary": "Fully open-source LLM with released weights, code, data, and training logs."
  },
  {
    "arxiv_id": "2403.14608",
    "title": "ReALM: Reference Resolution As Language Modeling",
    "domain": "aiml",
    "categories": ["cs.CL", "cs.AI"],
    "summary": "Resolves onscreen and conversational references using LLMs for device agents."
  },
  {
    "arxiv_id": "2402.14261",
    "title": "Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models",
    "domain": "aiml",
    "categories": ["cs.LG", "cs.CL"],
    "summary": "Hybrid architecture combining gated linear RNNs with local attention, matching transformer quality."
  },
  {
    "arxiv_id": "2401.14196",
    "title": "GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers",
    "domain": "aiml",
    "categories": ["cs.LG", "cs.CL"],
    "summary": "One-shot quantization method reducing LLM size to 3-4 bits with minimal accuracy loss."
  },
  {
    "arxiv_id": "2403.07691",
    "title": "Stealing Part of a Production Language Model",
    "domain": "security",
    "categories": ["cs.CR", "cs.LG", "cs.AI"],
    "summary": "Extracts internal architecture details from production LLM APIs through crafted queries."
  },
  {
    "arxiv_id": "2402.06132",
    "title": "SoK: Where's the Bug? A Study of Bug Localization Tools",
    "domain": "security",
    "categories": ["cs.CR", "cs.SE"],
    "summary": "Systematizes bug localization approaches and evaluates 23 tools on real-world CVEs."
  },
  {
    "arxiv_id": "2401.16727",
    "title": "A Survey of Side-Channel Attacks on Intel SGX",
    "domain": "security",
    "categories": ["cs.CR"],
    "summary": "Comprehensive analysis of side-channel attacks targeting Intel SGX enclaves."
  },
  {
    "arxiv_id": "2403.02783",
    "title": "SyzVegas: Beating Kernel Fuzzing Odds with Reinforcement Learning",
    "domain": "security",
    "categories": ["cs.CR", "cs.SE"],
    "summary": "RL-guided kernel fuzzer that outperforms Syzkaller in bug discovery rate."
  },
  {
    "arxiv_id": "2402.15483",
    "title": "BSIMM: An Empirical Study of 130 Software Security Programs",
    "domain": "security",
    "categories": ["cs.CR", "cs.SE"],
    "summary": "Large-scale study of enterprise security maturity across 130 organizations."
  },
  {
    "arxiv_id": "2403.14469",
    "title": "Reverse Engineering eBPF Programs: Challenges and Approaches",
    "domain": "security",
    "categories": ["cs.CR", "cs.OS"],
    "summary": "Novel techniques for reverse engineering eBPF bytecode in Linux kernel security."
  },
  {
    "arxiv_id": "2401.09577",
    "title": "WiFi-Based Keystroke Inference Attack Using Adversarial CSI Perturbation",
    "domain": "security",
    "categories": ["cs.CR", "cs.NI"],
    "summary": "Exploits WiFi channel state information to infer keystrokes from nearby devices."
  },
  {
    "arxiv_id": "2402.08787",
    "title": "Binary Code Similarity Detection via Graph Neural Networks",
    "domain": "security",
    "categories": ["cs.CR", "cs.SE", "cs.LG"],
    "summary": "GNN-based approach to detect similar binary functions across compilers and architectures."
  },
  {
    "arxiv_id": "2403.01218",
    "title": "Practical Exploitation of DNS Rebinding in IoT Devices",
    "domain": "security",
    "categories": ["cs.CR", "cs.NI"],
    "summary": "Demonstrates DNS rebinding attacks against 15 popular IoT devices in home networks."
  },
  {
    "arxiv_id": "2401.15491",
    "title": "GPU.zip: Side Channel Attacks on GPU-Based Graphical Data Compression",
    "domain": "security",
    "categories": ["cs.CR"],
    "summary": "First cross-origin pixel-stealing attack through GPU hardware data compression."
  },
  {
    "arxiv_id": "2402.03367",
    "title": "CryptoFuzz: Fully Automated Testing of Cryptographic API Misuse",
    "domain": "security",
    "categories": ["cs.CR", "cs.SE"],
    "summary": "Automated fuzzer detecting cryptographic API misuse patterns in Java applications."
  },
  {
    "arxiv_id": "2403.08946",
    "title": "Video Generation Models as World Simulators",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.AI", "cs.LG"],
    "summary": "Explores how video generation models learn physical world dynamics as implicit simulators."
  },
  {
    "arxiv_id": "2402.05929",
    "title": "V-JEPA: Video Joint Embedding Predictive Architecture",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.LG"],
    "summary": "Self-supervised video representation learning that predicts in latent space rather than pixel space."
  },
  {
    "arxiv_id": "2401.10020",
    "title": "AlphaGeometry: Solving Olympiad Geometry without Human Demonstrations",
    "domain": "aiml",
    "categories": ["cs.AI", "cs.LG"],
    "summary": "AI system solving IMO-level geometry problems through neurosymbolic reasoning."
  },
  {
    "arxiv_id": "2403.04132",
    "title": "Design2Code: How Far Are We From Automating Front-End Engineering?",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.CL", "cs.SE"],
    "summary": "Benchmarks multimodal LLMs on converting visual designs to functional HTML/CSS code."
  },
  {
    "arxiv_id": "2402.14905",
    "title": "YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information",
    "domain": "aiml",
    "categories": ["cs.CV"],
    "summary": "New YOLO architecture using programmable gradient information for better object detection."
  },
  {
    "arxiv_id": "2401.06066",
    "title": "MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation",
    "domain": "aiml",
    "categories": ["cs.CV", "cs.AI"],
    "summary": "Multi-stage video generation pipeline producing high-quality aesthetic videos from text."
  },
  {
    "arxiv_id": "2402.01680",
    "title": "Grandmaster-Level Chess Without Search",
    "domain": "aiml",
    "categories": ["cs.AI", "cs.LG"],
    "summary": "Transformer achieving grandmaster chess play through pure pattern recognition without tree search."
  },
  {
    "arxiv_id": "2403.04706",
    "title": "SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering",
    "domain": "aiml",
    "categories": ["cs.SE", "cs.CL", "cs.AI"],
    "summary": "LLM agent that autonomously fixes GitHub issues by interacting with code repositories."
  }
]