Researchers developed SQD-Agent, an AI-powered system that translates natural language into executable quantum chemistry experiments. The framework reduces expertise barriers by automating workflow orchestration on simulators and real quantum hardware.
#QuantumChemistry #LLMAgents #Research
#QuantumChemistry #LLMAgents #Research
SQD-Agent: LLM-Driven Framework for Quantum Chemistry Workflows
arxiv.org
October 13, 2026 at 6:28 AM
Researchers developed SQD-Agent, an AI-powered system that translates natural language into executable quantum chemistry experiments. The framework reduces expertise barriers by automating workflow orchestration on simulators and real quantum hardware.
#QuantumChemistry #LLMAgents #Research
#QuantumChemistry #LLMAgents #Research
A new arXiv paper proposes multi-agent session alternation for long-horizon machine learning engineering, framing it as a context-reset semi-Markov decision process to address "long-horizon deceleration" and…
#MLEAgents #LLMAgents #ContextEngineering #arxiv
https://arxiv.org/abs/2610.13494
#MLEAgents #LLMAgents #ContextEngineering #arxiv
https://arxiv.org/abs/2610.13494
October 12, 2026 at 8:01 AM
A new arXiv paper proposes multi-agent session alternation for long-horizon machine learning engineering, framing it as a context-reset semi-Markov decision process to address "long-horizon deceleration" and…
#MLEAgents #LLMAgents #ContextEngineering #arxiv
https://arxiv.org/abs/2610.13494
#MLEAgents #LLMAgents #ContextEngineering #arxiv
https://arxiv.org/abs/2610.13494
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 7, 2026 at 3:18 PM
Transect is an open source package built on Inspect Scout that helps evaluators retain observability over long-horizon LLM agent runs, surfacing behaviours worth investigation and grounding interpretations in transcripts. By…
#OpenSourceAI #LLMAgents #AI #Inspect
https://arxiv.org/abs/2610.08364
#OpenSourceAI #LLMAgents #AI #Inspect
https://arxiv.org/abs/2610.08364
October 9, 2026 at 10:01 PM
Transect is an open source package built on Inspect Scout that helps evaluators retain observability over long-horizon LLM agent runs, surfacing behaviours worth investigation and grounding interpretations in transcripts. By…
#OpenSourceAI #LLMAgents #AI #Inspect
https://arxiv.org/abs/2610.08364
#OpenSourceAI #LLMAgents #AI #Inspect
https://arxiv.org/abs/2610.08364
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 7, 2026 at 3:18 PM
ReCodeAgent is a multi-agent system for translating and validating large code repositories across any programming language pair, going beyond the single-pair focus of prior work. Let’s see if it can hold…
#devtools #codetranslation #LLMagents #softwareengineering
https://arxiv.org/abs/2604.07341
#devtools #codetranslation #LLMagents #softwareengineering
https://arxiv.org/abs/2604.07341
October 9, 2026 at 10:01 PM
ReCodeAgent is a multi-agent system for translating and validating large code repositories across any programming language pair, going beyond the single-pair focus of prior work. Let’s see if it can hold…
#devtools #codetranslation #LLMagents #softwareengineering
https://arxiv.org/abs/2604.07341
#devtools #codetranslation #LLMagents #softwareengineering
https://arxiv.org/abs/2604.07341
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 7, 2026 at 12:40 AM
A new unsupervised method called OAT tackles failure attribution in LLM-based agentic systems by training only on successful trajectories and using one-class learning with neural controlled differential…
#LLMAgents #PromptEngineering #AIDebugging #GenerativeAI
https://arxiv.org/abs/2607.12747
#LLMAgents #PromptEngineering #AIDebugging #GenerativeAI
https://arxiv.org/abs/2607.12747
October 14, 2026 at 2:01 PM
A new unsupervised method called OAT tackles failure attribution in LLM-based agentic systems by training only on successful trajectories and using one-class learning with neural controlled differential…
#LLMAgents #PromptEngineering #AIDebugging #GenerativeAI
https://arxiv.org/abs/2607.12747
#LLMAgents #PromptEngineering #AIDebugging #GenerativeAI
https://arxiv.org/abs/2607.12747
New arXiv paper ReCast proposes a step representation learning method to improve failure attribution in LLM-based agent systems by transforming hidden states from a frozen LLM into attribution-oriented representations.
#AI #LLMAgents #Research #ArXiv
https://arxiv.org/abs/2610.11334
#AI #LLMAgents #Research #ArXiv
https://arxiv.org/abs/2610.11334
October 10, 2026 at 12:01 PM
New arXiv paper ReCast proposes a step representation learning method to improve failure attribution in LLM-based agent systems by transforming hidden states from a frozen LLM into attribution-oriented representations.
#AI #LLMAgents #Research #ArXiv
https://arxiv.org/abs/2610.11334
#AI #LLMAgents #Research #ArXiv
https://arxiv.org/abs/2610.11334
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 7, 2026 at 12:21 AM
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 7, 2026 at 12:39 AM
New arXiv work proposes REVEAL, a training-free framework that reverse engineers reusable control signals from frontier-model traces to guide frozen open-source agents. The approach treats successful trajectories…
#OpenSourceAI #LLMAgents #Distillation #AIResearch
https://arxiv.org/abs/2610.16288
#OpenSourceAI #LLMAgents #Distillation #AIResearch
https://arxiv.org/abs/2610.16288
October 14, 2026 at 2:01 PM
New arXiv work proposes REVEAL, a training-free framework that reverse engineers reusable control signals from frontier-model traces to guide frozen open-source agents. The approach treats successful trajectories…
#OpenSourceAI #LLMAgents #Distillation #AIResearch
https://arxiv.org/abs/2610.16288
#OpenSourceAI #LLMAgents #Distillation #AIResearch
https://arxiv.org/abs/2610.16288
Researchers are using software release history to study what makes desktop apps easier for LLM agents, releasing DeskIF-Bench with 255 tasks across six applications to measure how interface changes affect agent…
#devtools #LLMagents #softwareengineering #AI
https://arxiv.org/abs/2610.15765
#devtools #LLMagents #softwareengineering #AI
https://arxiv.org/abs/2610.15765
October 14, 2026 at 10:02 PM
Researchers are using software release history to study what makes desktop apps easier for LLM agents, releasing DeskIF-Bench with 255 tasks across six applications to measure how interface changes affect agent…
#devtools #LLMagents #softwareengineering #AI
https://arxiv.org/abs/2610.15765
#devtools #LLMagents #softwareengineering #AI
https://arxiv.org/abs/2610.15765
Bench2Robust is a new framework that benchmarks how well tool-using agents handle tool failures, schema drift, and unavailable services during deployment. Testing 7 models across 10 task slices, 69 of 70 model-subset pairs…
#AI #LLMAgents #DevTools #Benchmarking
https://arxiv.org/abs/2608.11977
#AI #LLMAgents #DevTools #Benchmarking
https://arxiv.org/abs/2608.11977
October 15, 2026 at 2:01 AM
Bench2Robust is a new framework that benchmarks how well tool-using agents handle tool failures, schema drift, and unavailable services during deployment. Testing 7 models across 10 task slices, 69 of 70 model-subset pairs…
#AI #LLMAgents #DevTools #Benchmarking
https://arxiv.org/abs/2608.11977
#AI #LLMAgents #DevTools #Benchmarking
https://arxiv.org/abs/2608.11977
EvoDrive introduces an LLM-based agentic framework using a simulator-grounded actor-critic architecture to evolve safety-critical driving scenarios, aiming to balance adversariality and realism beyond handcrafted…
#AI #AutonomousDriving #AISafety #LLMAgents
https://arxiv.org/abs/2606.03678
#AI #AutonomousDriving #AISafety #LLMAgents
https://arxiv.org/abs/2606.03678
October 12, 2026 at 4:01 PM
EvoDrive introduces an LLM-based agentic framework using a simulator-grounded actor-critic architecture to evolve safety-critical driving scenarios, aiming to balance adversariality and realism beyond handcrafted…
#AI #AutonomousDriving #AISafety #LLMAgents
https://arxiv.org/abs/2606.03678
#AI #AutonomousDriving #AISafety #LLMAgents
https://arxiv.org/abs/2606.03678
A new arXiv paper argues self-evolving LLM agents in credit pipelines should be confined to the runtime harness, with model weights fixed, so every change is a reviewable diff with a test and hash-chained admission record.…
#AIResearch #LLMAgents #AISafety #Arxiv
https://arxiv.org/abs/2610.10629
#AIResearch #LLMAgents #AISafety #Arxiv
https://arxiv.org/abs/2610.10629
October 10, 2026 at 4:00 AM
A new arXiv paper argues self-evolving LLM agents in credit pipelines should be confined to the runtime harness, with model weights fixed, so every change is a reviewable diff with a test and hash-chained admission record.…
#AIResearch #LLMAgents #AISafety #Arxiv
https://arxiv.org/abs/2610.10629
#AIResearch #LLMAgents #AISafety #Arxiv
https://arxiv.org/abs/2610.10629
OpenAI just dropped the Decisions API—now LLMs can plan their own steps, streamline workflow automation, and boost model evaluation. Agent builders, this could change how you design intelligent agents. Dive in to see what’s possible! #OpenAIDecisions #LLMAgents #WorkflowAutomation
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October 13, 2026 at 1:13 AM
OpenAI just dropped the Decisions API—now LLMs can plan their own steps, streamline workflow automation, and boost model evaluation. Agent builders, this could change how you design intelligent agents. Dive in to see what’s possible! #OpenAIDecisions #LLMAgents #WorkflowAutomation
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#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 6, 2026 at 6:04 PM
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 6, 2026 at 11:00 PM
The new MemCalib benchmark shows frontier open- and closed-source LLMs often over- or under-use agent memory, and common post-training methods like GRPO and on-policy self-distillation reinforce that skewed behavior. Worth…
#LLMAgents #OpenSourceAI #AIResearch
https://arxiv.org/abs/2609.24259
#LLMAgents #OpenSourceAI #AIResearch
https://arxiv.org/abs/2609.24259
October 10, 2026 at 12:01 AM
The new MemCalib benchmark shows frontier open- and closed-source LLMs often over- or under-use agent memory, and common post-training methods like GRPO and on-policy self-distillation reinforce that skewed behavior. Worth…
#LLMAgents #OpenSourceAI #AIResearch
https://arxiv.org/abs/2609.24259
#LLMAgents #OpenSourceAI #AIResearch
https://arxiv.org/abs/2609.24259
LLM agents favor their own group mainly because they observe members favoring each other, not because of the group label itself, which loses its effect once giving points has a cost. Across about 4,400 simulated societies and…
#AI #LLMAgents #OpenSourceAI #ArXiv
https://arxiv.org/abs/2610.11008
#AI #LLMAgents #OpenSourceAI #ArXiv
https://arxiv.org/abs/2610.11008
October 9, 2026 at 6:01 AM
LLM agents favor their own group mainly because they observe members favoring each other, not because of the group label itself, which loses its effect once giving points has a cost. Across about 4,400 simulated societies and…
#AI #LLMAgents #OpenSourceAI #ArXiv
https://arxiv.org/abs/2610.11008
#AI #LLMAgents #OpenSourceAI #ArXiv
https://arxiv.org/abs/2610.11008
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 6, 2026 at 6:29 PM
#AI #ArtificialIntelligence #AIEngineering #GenerativeAI #LLM #AIAgents #AgenticAI #LLMAgents #MCP #ModelContextProtocol #ToolCalling #RAG #SoftwareEngineering #FullStack #Backend #TypeScript #NextJS #NestJS #PostgreSQL #SaaS #Automation #TechStartup #BuildInPublic #IndieHackers
October 6, 2026 at 11:00 PM
A new arXiv paper proposes a closed-loop benchmark for evaluating LLM coding agents on embedded firmware, emphasizing iterative build-and-test behavior over static code quality. It contains five embedded-control…
#arxiv #llmagents #embedded #softwareengineering
https://arxiv.org/abs/2610.11447
#arxiv #llmagents #embedded #softwareengineering
https://arxiv.org/abs/2610.11447
October 9, 2026 at 10:01 AM
A new arXiv paper proposes a closed-loop benchmark for evaluating LLM coding agents on embedded firmware, emphasizing iterative build-and-test behavior over static code quality. It contains five embedded-control…
#arxiv #llmagents #embedded #softwareengineering
https://arxiv.org/abs/2610.11447
#arxiv #llmagents #embedded #softwareengineering
https://arxiv.org/abs/2610.11447
Researchers propose MASTIF, a baseline evaluation framework for LLM-based agentic web technologies, testing 3 LLMs, 3 protocols, and 4 frameworks on 300 Mind2Web tasks. Results suggest the choice of stack…
#AIInfrastructure #LLMAgents #AIAgents #TechStack
https://arxiv.org/abs/2610.13703
#AIInfrastructure #LLMAgents #AIAgents #TechStack
https://arxiv.org/abs/2610.13703
October 12, 2026 at 8:01 AM
Researchers propose MASTIF, a baseline evaluation framework for LLM-based agentic web technologies, testing 3 LLMs, 3 protocols, and 4 frameworks on 300 Mind2Web tasks. Results suggest the choice of stack…
#AIInfrastructure #LLMAgents #AIAgents #TechStack
https://arxiv.org/abs/2610.13703
#AIInfrastructure #LLMAgents #AIAgents #TechStack
https://arxiv.org/abs/2610.13703