Recent efforts to scale tool-use post-training have largely centered on the synthesis of executable environments, which constitute only one component of a broader agentic interaction system comprising the environment, task, agent harness, and evaluator. Scaling environments in isolation, however, does not guarantee com...
Bo Mao, Hang He, Lin-Ting Wang et al.
· 0 citations
Save
{ copied = true; setTimeout(() => copied = false, 1500) })"
class="icon-btn" aria-label="Copy link">
{ copied = 'apa'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy APA
Copied ✓
{ copied = 'mla'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy MLA
Copied ✓
{ copied = 'bibtex'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy BibTeX
Copied ✓
35B \texttt{SkillGym-Agent} reaches 51.47\% on skill-assisted SkillsBench, exceeding reported scores for Claude Sonnet 4.6, GPT-5.4 Mini, and DeepSeek V4 Pro, suggesting reusable procedural competence.
Zhi-Long Ge, Yu-Ting Shao, Yu-Tao Yang et al.
· 0 citations
Save
{ copied = true; setTimeout(() => copied = false, 1500) })"
class="icon-btn" aria-label="Copy link">
{ copied = 'apa'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy APA
Copied ✓
{ copied = 'mla'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy MLA
Copied ✓
{ copied = 'bibtex'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy BibTeX
Copied ✓
Preprint
Jul 2026
This work proposes \textsc{AutoMem}, a text-gradient recursive self-improvement framework for task-adaptive memory architecture search that consistently discovers task-adaptive memory architectures that outperform the strongest human-designed memory baselines.
Lin-Ge Du, Jie Zhou, Yuxuan Cai et al.
· 0 citations
Save
{ copied = true; setTimeout(() => copied = false, 1500) })"
class="icon-btn" aria-label="Copy link">
{ copied = 'apa'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy APA
Copied ✓
{ copied = 'mla'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy MLA
Copied ✓
{ copied = 'bibtex'; setTimeout(() => { copied = null; open = false }, 1000) })"
class="flex w-full items-center justify-between rounded-lg px-3 py-2 text-left text-sm hover:bg-gray-100 dark:hover:bg-ink-800">
Copy BibTeX
Copied ✓