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11 results for “LLM agents”
LLM Agents Factory: Retrieval of Domain-Specific LLM Agents
arXiv:2608.09934v1 Announce Type: new Abstract: Large language model (LLM) agents improve task performance by decomposing problems into role-specialized behaviors. However, their practical deployment is often limited by the computational cost and instability associated with the on-the-fly agent design for each user request. To address this, we present LLM Agents Factory, a retrieval-based framework that constructs domain-specific and Wikipedia-grounded agents on demand using a base of over 20K p
Aug 13, 2026
Controlled Memory Interference in Continual LLM Agents
Researchers introduce Controlled Memory Interference (CMI), a diagnostic and data-generation framework to study how long-term memory in continual LLM agents evolves under competing memory relationships — revealing that interference, not just scale, critically impacts update plasticity and stability.
Aug 11, 2026
Zero-Mem: Zero-Token Memory Operations for LLM Agents
A forum post on Hacker News titled 'Zero-Mem: Zero-Token Memory Operations for LLM Agents' presents an unverified technical concept without descriptive content, context, or evidence — making it functionally inert as a news or technical signal.
Aug 5, 2026
HyperAgent: Planning and Acting over Tool-Schema Hypergraphs for Tool-Use LLM Agents
HyperAgent is a new LLM agent framework that models tool interactions as a hypergraph of input/output schemas to improve planning efficiency and reduce redundant API calls and token usage in complex task execution.
Aug 5, 2026
AI doomers Vs AI acelerationists
A Reddit user seeks community input to understand the ideological divide between 'AI doomers' and 'AI accelerationists' ahead of an upcoming meeting with people holding more extreme views.
Aug 3, 2026
SF-AMS: Strategic Forgetting for Structured Memory in LLM Agent
A new memory management framework called SF-AMS introduces utility-driven 'strategic forgetting' to improve long-context reasoning in LLM agents by dynamically prioritizing stable, entity-consistent information and filtering noise.
Jul 28, 2026
Agentic Evaluation of Copyright Law Compliance
Researchers introduced Copyright-Bench, a new benchmark to evaluate whether LLM agents comply with copyright law when performing commercial tasks like website development or pitch deck creation, finding that agents frequently select copyrighted content over legal public-domain alternatives — especially under time pressure or specific user prompts.
Jul 27, 2026
Toward User-Conditioned Evaluation of Personal LLM Agents under Temporal Interventions
A research paper identifies a gap in how personal LLM agents are evaluated—arguing that current benchmarks fail to test how agent capabilities interact dynamically across time and user-specific states—and proposes a minimal benchmark design with four formal conditions.
Jul 27, 2026
From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents
Researchers propose EvoSOP, a framework enabling LLM agents to automatically synthesize atomic tool actions into reusable Standard Operating Procedures (SOPs), improving task success rates and reducing interaction rounds in experimental settings.
Jul 10, 2026
From Signals to Structure: How Memory Architecture Drives Language Emergence in LLM Agents
A new arXiv preprint demonstrates that memory architecture—not just channel capacity—determines whether LLM agents can reliably invent and sustain shared language in signaling games, with persistent private notebooks enabling robust coordination even at high capacity.
Published Jul 2, 2026 · Analyzed Jul 5, 2026
A system-level approach to prompt injection: separating instruction and data channels in LLM agents [P]
A system-level approach to prompt injection has been proposed to mitigate failure modes in LLM systems.
Published Jul 1, 2026 · Analyzed Jul 6, 2026