Hubmesh, a new open-source project, introduces a local-first multi-hop retrieval system that combines Chroma vector search with an entity graph and Personalized PageRank, achieving 75.2% supporting-fa…
A new open-source library, hubmesh, adds a graph layer on top of Qdrant to answer multi-hop questions that stymie vector search. The library builds an entity-document graph at index time and uses Pers…
A new arXiv preprint (2608.00585v1) shows that per-chunk verification fails on multi-hop retrieval-augmented generation, with entailment scoring reaching only 0.643, 0.523, and 0.560 AUC on HotpotQA, …
A new family of graph theory-based defenses called TopoGuard, introduced by researchers in a preprint on arXiv, catches 21 times more split-knowledge attacks on Retrieval Augmented Generation (RAG) sy…
A developer built raven-retrieval, an open-source framework that benchmarks 19 retrieval pipelines on BEIR datasets with Bonferroni-corrected significance tests. The key finding is that top pipelines …
A new benchmark and training set called SelectBench, introduced by researchers in arXiv:2607.20090v1, shows that reinforcement learning via DAPO can modestly improve selective evidence adoption in ret…
Researchers at arXiv propose Contextual Information-Gain Policy Optimization (CIGPO) to fix a zero-advantage lock-in failure in outcome-only reinforcement learning for multi-turn evidence-reading agen…
A new approach using Quadratic Unconstrained Binary Optimization (QUBO) for evidence selection in retrieval-augmented generation (RAG) systems achieves competitive exact-match and token-F1 performance…
A new study on memory-managed long-context attention achieves a perfect 1.000 score on Track A, a controlled retrieval task, compared to a 0.333 baseline, and outperforms dense retrieval methods by up…
DeepSearch-Evolve introduces a self-distillation framework for training web agents in a controlled environment, achieving state-of-the-art results on benchmarks like BrowseComp, GAIA, and HotpotQA wit…
Researchers introduced DeepSearch-World, a deterministic and verifiable environment for training web agents, and DeepSearch-Evolve, a self-distillation framework that enables agents to improve from th…
AWS announced HippoRAG, a neurobiologically inspired retrieval augmented generation framework using Amazon Bedrock, Amazon Neptune, and Personalized PageRank to improve multi-hop reasoning in large la…
Researchers introduced Contrastive Reflection, an iterative prompt-optimization framework for agentic information retrieval workflows, which uses error-anchored behavioral slices and contrastive examp…
Maneshwar, developer of git-lrc, explains the ReAct (Reasoning + Acting) prompting pattern from Yao et al., 2022. ReAct interleaves reasoning traces with actions like search or lookup, allowing langua…
Researchers introduced Decoupled Search Grounding (DSG), a vendor-agnostic architecture that separates search from reasoning in LLM agents, enabling independent control over retrieval policy, provider…
Researchers at arXiv propose Telegraph English, a readable symbolic format for context compression that rewrites retrieved passages into structured entity-relation statements. In experiments on multi-…
Researchers have identified a new failure mode in multi-step agentic retrieval-augmented generation (RAG) systems called cascading hallucination, where errors from early pipeline stages propagate and …
Headroom, a new macOS menu bar app, reduces Claude Code token usage by approximately 50% by locally trimming prompt bloat and boilerplate before inputs reach the model. The tool processes all data on …
Researchers have demonstrated that compressing tool schemas by 44-50% enables agentic retrieval-augmented generation (RAG) systems to function under tight context budgets, where uncompressed definitio…
Researchers introduced parallel context compaction for long-horizon LLM agent serving, addressing the problem of growing conversation histories exceeding context windows. The method provides fine-grai…