Assembly Graph
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Show HN: Mnemo – local-first AI memory layer for any LLM (Rust, SQLite,petgraph)
Local-first AI memory layer for any LLM. Persistent knowledge graph, entity extraction, semantic retrieval — no cloud required. Most LLMs forget everything the moment a conversation ends.
PARSE: Part-Aware Relational Spatial Modeling
Announce Type: replace Abstract: Inter-object relations underpin spatial intelligence, yet existing representations -- linguistic prepositions or object-level scene graphs -- are too coarse to specify which regions actually support, contain, or contact one another, leading to ambiguous and physically inconsistent layouts. To address these ambiguities, a part-level formulation is needed; therefore, we introduce PARSE, a framework that explicitly models how object parts interact to determine...
Lignin to adipic acid in a high-yield chemical and biological redox process
Abstract Viable manufacturing pathways to produce bio-based chemicals from renewable feedstocks, such as lignin derived from plant biomass, are needed to decarbonize the chemicals manufacturing sector. Converting the recalcitrant lignin polymer to valuable bioproducts remains a longstanding challenge in biorefining, with the highest reported single-product yield from lignin currently around 20 wt% (refs. Most existing lignin depolymerization strategies target aryl–ether bond cleavage, which...
Towards Efficient Synthesis of Quantum Graph States by Fusing Graph Motifs
Announce Type: cross Abstract: Photonic graph states with advanced topologies can enable measurement-based quantum computing, distributed quantum sensing, and quantum interconnects. However, the efficient generation of photonic graph states is limited by the probabilistic nature of photonic entangling operations and the exponential dependence of generation rate on resource cost. In this work, we study photonic graph state synthesis as a cost-aware decomposition problem, exploiting local...
Narrative Knowledge Weaver: Narrative-Centric Retrieval-Augmented Reasoning for Long-Form Text Understanding
arXiv:2606.05724v1 Announce Type: new Abstract: Long-form narrative QA requires reasoning over evolving story worlds rather than isolated passages: answers may depend on earlier goals, changing character states, social relations, causal triggers, temporal position, and later consequences. Existing retrieval and graph-augmented generation methods improve evidence access, but their units--chunks, entities, relations, summaries, or tool actions--do not directly encode how evidence functions in...
Muses: Designing, Composing, Generating Nonexistent Fantasy 3D Creatures without Training
arXiv:2601.03256v2 Announce Type: replace Abstract: We present Muses, the first training-free method for fantastic 3D creature generation in a feed-forward paradigm. Previous methods, which rely on part-aware optimization, manual assembly, or 2D image generation, often produce unrealistic or incoherent 3D assets due to the challenges of intricate part-level manipulation and limited out-of-domain generation. In contrast, Muses leverages the 3D skeleton, a fundamental representation of...
Locality-Aware Automatic Differentiation on the GPU for Mesh-Based Computations
arXiv:2509.00406v3 Announce Type: replace Abstract: We present a GPU-based system for automatic differentiation (AD) of functions defined on triangle meshes, designed to exploit the locality and sparsity in mesh-based computation. Our system evaluates derivatives using per-element forward-mode AD, confining all computation to registers and shared memory and assembling global gradients, sparse Jacobians, and sparse Hessians directly on the GPU. By avoiding global computation graphs,...
FLOWREADER: Min-Cost Flow Optimization for Multi-Modal Long Document Q&A
arXiv:2606.07235v1 Announce Type: new Abstract: Long, multimodal documents force retrieval-augmented systems to assemble answers from evidence fragmented across text, tables, and slides broken across cells in a long table, spread over multiple slides, or split between a figure and its discussion. Top-$k$ chunk retrieval treats each fragment independently and cannot represent how evidence connects.
FLOWREADER: Min-Cost Flow Optimization for Multi-Modal Long Document Q&A
arXiv:2606.07235v2 Announce Type: replace Abstract: Long, multimodal documents force retrieval-augmented systems to assemble answers from evidence fragmented across text, tables, and slides broken across cells in a long table, spread over multiple slides, or split between a figure and its discussion. Top-$k$ chunk retrieval treats each fragment independently and cannot represent how evidence connects. We introduce FLOWREADER, which reframes evidence assembly as a min-cost flow problem on a...
Absorbing Complexity: An Interaction-Native Knowledge Harness for Financial LLM Agents
arXiv:2606.01886v1 Announce Type: new Abstract: Financial AI agents often fail for a simple reason: they make users carry the complexity. A user must repeatedly restate goals, risk preferences, portfolio context, past judgments, and shifting market assumptions, while the agent answers, retrieves, acts, and forgets. In finance, this is not just inconvenient.