… The following papers were recommended by the Semantic Scholar API DR-Venus: Towards Frontier Edge-Scale Deep Research Agents with Only 10K Open Data 2026 MTA-Agent: An Open Recipe for Multimodal Deep Search Agents 2026 GraphWalker: Agentic Knowledge Graph Question Answering via Synthetic Trajectory… …
… The following papers were recommended by the Semantic Scholar API OpenSeeker: Democratizing Frontier Search Agents by Fully Open-Sourcing Training Data 2026 Marco DeepResearch: Unlocking Efficient Deep Research Agents via Verification-Centric Design 2026 DR-Venus: Towards Frontier Edge-Scale Deep R… …
… The following papers were recommended by the Semantic Scholar API CoSearch: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search 2026 A Survey of Reasoning-Intensive Retrieval: Progress and Challenges 2026 PAR$^2$-RAG: Planned Active Retrieval and Reasoning… …
… The following papers were recommended by the Semantic Scholar API Towards Long-horizon Agentic Multimodal Search 2026 Mind DeepResearch Technical Report 2026 OASES: Outcome-Aligned Search-Evaluation Co-Training for Agentic Search 2026 SAKE: Self-aware Knowledge Exploitation-Exploration for Grounded… …
… AI-generated summary Multimodal deep search requires an agent to solve open-world problems by chaining search, tool use, and visual reasoning over evolving textual and visual context. …
… However, when paired with a search-based training procedure that maintains and prunes multiple candidate contexts , active information seeking delivers consistent and substantial gains. …
… Classical fingerprint-based plagiarism detectors based on fingerprinting, such as Winnowing , remain highly effective, yet the inspection requires comparing fragments of code to the entire training set, and their linear-time search makes them impractical for the billion-scale corpora used to train … …
… Motivated by the "search, select, update" principle underlying GDS, we propose Dynamic Latent Routing DLR , a language-model post-training method that jointly learns discrete latent codes , routing policies , and model parameters through dynamic search in a single training stage. …
… AI-generated summary Clinical reasoning demands multi-step interactions -- gathering patient history, ordering tests, interpreting results, and making safe treatment decisions -- yet a unified training environment provides the breadth of clinical domains and specialized tools to train generalizable… …
… Thanks! is the trained model now open source and / or available to the public? https://huggingface.co/blog/sionic-ai/claude-code-skills-training Nice work about the demo getting Claude Code to fine-tune an open LLM. But the researchers from Sionic AI already do most of their work with Claude Code. …