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Ablations show how to evaluate coding-agent harnesses
A paper published on September 26, 2026 reports 176 configurations tested on two benchmarks and describes differing effects from context summarization and explicit planning.
AI R&D agents need to revisit training strategy
A study published on August 22, 2026, analyzed 1,338 post-training trajectories. The overall strategy changed in 74 of 3,557 adjacent experiments.
- 19 days ago openresearch.sh
Agents for reproducing research and provisioning GPUs
OpenResearch is described as a tool that uses agents to reproduce paper results and provision cloud GPUs. The author says it reproduced their paper end to end.
Agents can decide when to seek more context
An article published on August 22, 2026 models interactive agents’ choice between acting on assumptions and seeking context, accounting for the costs of those actions.
Agents that update their model of the environment during inference
A post published on June 30, 2026, about ARC-AGI-3 says that learning during inference leads agents to build models of rules and mechanics, updating them with new evidence.
AREAL2.0 links real tasks to agent improvement
Published on July 10, 2026, the article presents a continuous-learning architecture that turns real tasks into training data and triggers policy updates.
Self-improvement in agents: making adaptation controllable
A survey published on July 16, 2026 examines modern agentic systems as foundation models integrated with prompts, memory, and tools. Its system-level view helps identify where updates happen and how to make them controllable.
Autodata structures agents to create and evaluate datasets
Published on June 25, 2026, the material presents Autodata, a staged method in which AI agents create and analyze training and evaluation data, then apply meta-optimization.
Autodata generates training data with agent loops
Published on July 6, 2026, the Autodata method uses weak and strong solvers to select questions that distinguish model performance.
Automating scientific review while keeping human oversight
The article, published on June 29, 2026, frames scientific review at scale as a systems challenge and proposes four levels of collaboration between AI and humans.
AutoMem explores agent-managed memory
A post published on July 6, 2026 describes a paper on agents that write, search, and organize notes, with reported 2x to 4x gains in long games.
Autoresearch agent beats a manual harness after eight days
A post published on July 14, 2026, reports that an autoresearch agent improved over eight days and outperformed a manually tuned harness on benchmarks excluded from training.
- 19 days ago victorchen96.github.io
AutoResearch automates reinforcement learning experiments
A post published on June 18, 2026 describes an agent that planned and ran GPU-based reinforcement learning experiments, including code writing, debugging, and summarizing conclusions.
- 19 days ago reddit.com
Benchmark compares seven self-hosted memory providers for Hermes Agent
Published on August 9, 2026, the community benchmark compares seven self-hosted memory providers for Hermes Agent, using 71,060 conversation turns and 3,750 questions about changing facts.
BINEVAL makes LLM evaluations more interpretable
Published on June 27, 2026, the post describes a binary-question evaluation that matched or outperformed UniEval and G-Eval on three datasets without training.
- 19 days ago lab.einsia.ai
BrowserBC turns human browsing into reusable agent skills
Published on July 7, 2026, the post describes BrowserBC, which turns human browsing traces into reusable skill cards. It reports gains in task success, retrieval, and generalization across sites.
Local hybrid search for agents: what zg offers
On September 2, 2026, Alibaba's Zvec team announced zg, a local search tool combining semantic search, BM25, hybrid search, and rg, with support for popular agents.
- 19 days ago github.com
Buzz publishes a specification for agent memory
On July 28, 2026, Buzz published the NIP-AE specification for its memory feature, aiming to support implementation and interoperability.
Iterative code improves scientific forecasts
A study published in Nature assessed combinations of forecasting methods across six fields: 24 of 55 combinations outperformed both methods from which they originated.
- 19 days ago openreview.net
How agents can learn from interaction traces
A survey published on June 27, 2026, discusses how agents in production turn interaction traces into durable capabilities, from self-evolution to meta-evolution.
How to evaluate AI agent memory
An article published on June 26, 2026 examines agent memory systems and notes that existing evaluations often treat memory as a black box.
Evaluating rewards for coding agents
A July 4, 2026 post describes four reward signals for coding agents and discusses failures and corrections that can help detect reward hacking.
- 19 days ago alphaxiv.org
How coding agents learn from software development experience
Published on August 9, 2026, the survey analyzes 108 systems that use development interactions to adapt memory, workflows, tools, or model parameters.
Validating results generated by research agents
An arXiv paper published on September 1, 2026, reports that checking manuscript claims against execution logs reduced the reported rate of serious errors to 4%.
How to verify rewards for coding agents
A paper published on July 11, 2026 examines four reward-verification designs and finds no single solution to the challenge of reliably evaluating coding agents.
DiscoBench tests search agents on ambiguous requests
Published on June 29, 2026, DiscoBench evaluates whether language-model search agents can handle vague, underspecified, or factually incorrect requests in multi-step retrieval and reasoning tasks.
A shell prompt mismatch increased latency in DSH
A post published on August 17, 2026 reports that different prompts in two DSH shell tools triggered a 3.5-second timeout; a change reduced one command's time from 3,600 ms to 158 ms.
Dockerless proposes verifying patches without execution
Published on June 30, 2026, the paper describes a verifier that assesses coding-agent patches without running them. The proposal targets selecting SFT trajectories and providing rewards for RL, as an alternative to setting up repository-specific environments.
EvoRec proposes agents to optimize recommendations
Published on June 30, 2026, the paper presents a multi-agent framework intended to reduce manual optimization of recommendation systems by retaining methods across iterations and exploring ideas beyond a predefined search space.
Git as shared memory for research agents
A post published on September 17, 2026 describes agents recording verifiable contributions in a searchable Git history to share results and reduce repeated experiments.
- 19 days ago github.com
Harness expands browser and computer options for agents
Version v0.1.6-alpha.1, published on September 15, 2026, adds persistent terminals, multiple tabs, MCP support, and experimental options for browser and computer use.
- 19 days ago lilianweng.github.io
Harness engineering and the limits of AI self-improvement
In an article published on July 7, 2026, Lilian Weng examines recursive self-improvement and identifies harness design and optimization as a practical starting point, while discussing evaluation, diversity, and security challenges.
HarnessBank: evolving agent harnesses
An article published on July 17, 2026 describes a method for improving agents by changing prompts, tools, and control loops around the model.
HASTE shows how to organize skills for ML agents
The material on HASTE reports that, across eight competitions, hierarchical skill loading achieved a 100% medal rate, compared with 62.5% for flat loading.
- 19 days ago arxivb.org
JAZ and evaluating recursive agent loops
Published on September 26, 2026, the post describes JAZ, a minimalist framework that uses a single recursive primitive for agent loops, and claims it may outperform Letta and ACE at lower cost.
JAZ explores agents built around one code primitive
Published on September 26, 2026, the post describes the JAZ framework and reports results on StuLife and AppWorld, with lower costs than the compared approaches.
JIT-Agent adapts agent harnesses to each task
The article on JIT-Agent describes on-demand synthesis and evolution of harnesses for LLM-based agents, using modules for memory, planning, actions, and tools. Published August 27, 2026.
MemoHarness adapts agents using execution history
Published on July 17, 2026, the work presents a method that adjusts six dimensions of an agent harness using prior executions. On a shell-agent benchmark, it scored 0.806, compared with 0.722 for the strongest fixed-harness baseline.
Agent memory with a frozen model
In a post published on August 26, 2026, Recuris describes two memory loops and a fixed meta-agent that proposes repairs based on execution traces, without changing model weights.
Proactive memory for long-horizon agents
A paper describes a separate memory agent that maintains structured records and decides when to present reminders to an action agent. The approach was evaluated on Terminal-Bench 2.0 and tau-squared-Bench.
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