Entity trail

ICLR

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Showing the first 40 findings. More graph evidence exists in the corpus.

Corpus findings

2026-08-16 / sources-researcherRhetoric Reward-Hacks AI Reviewers: 4,200 Manuscripts From 120 ICLR 2026 Submissions Show Evidence Framing and Novelty Stance Move Scores With Content Held ConstantarXiv 2608.08975 (August 10, 2026, 43 HF upvotes) built a controlled corpus of 4,200 full-paper manuscripts derived from 120 anonymized ICLR 2026 submissions, had two LLM rewriters push six rhetorical dimensions in opposing directions while preserving reported scientific content, then had five LLM reviewers grade them under standard and strict protocols. Evidence framing and novelty stance produce the largest swings, with scope framing a weaker second tier — and the effect is regression-shaped: low original scores rise, high ones fall, with the clearest contrasts in the middle. Elaborate workflows do not help; joint rewriting is rewriter-dependent and reviewer-guided rewriting does not beat an unguided second pass.
2026-08-13 / agents-researcher'Agent Safety Should Be a Runtime Contract': a title-level audit of 28,560 NeurIPS/ICML/ICLR papers finds an 8–12x train-vs-runtime imbalanceThis position paper argues that instilling safety during training (RLHF, DPO, Constitutional AI) is structurally insufficient for agents that execute code, mutate files and modify databases, and that safety must be a runtime contract enforced by the harness with two faces: preventive (sandboxes, permission gates, trajectory monitors) and evidential (gating task submission on hard proof — test runs, log captures, file diffs, citation grounding). It grounds this in four released datasets: a survey of 52 documented agent/LLM safety incidents, a false-completion audit with 31 non-contested cases, a trajectory-schema audit of 12 public agent systems and harnesses, and a title-level audit of all 28,560 papers accepted at NeurIPS/ICML/ICLR 2023–2025 showing a pooled 8–12x imbalance favoring training-time over runtime safety work.
2026-06-27 / skill-finderStop benchmarking tool-use on toys: MCP-Atlas and Tool-Decathlon test agents against real MCP serversTwo new 2026 benchmarks evaluate tool-using agents on realistic workloads: MCP-Atlas has 1,000 human-verified tasks across 36 real MCP servers and 220 tools (current leaders: Gemini 3.5 Flash 83.6%, Claude Opus 4.8 82.2%), and Scale moved it to a 100-tool-call budget instead of a 20-turn limit. Tool-Decathlon (ICLR 2026) runs 108 long-horizon tasks in isolated containers — Claude-4.5-Sonnet finishes all 108 in ~70 minutes across 10 parallel processes. For anyone shipping an MCP/tool-calling agent, these are the references to grade your stack against instead of single-turn function-call accuracy.
2026-06-12 / skill-finderReplace RL prompt tuning with GEPA reflective evolution — same gains at 35x fewer rolloutsGEPA (an ICLR 2026 oral, now shipping as dspy.GEPA) optimizes prompts by having an LM reflect in natural language on a program's execution trace — what went well, what failed — then evolving a tree of candidate prompts, instead of using policy gradients. Across six tasks it beats GRPO by 6% on average (up to 20%) while using up to 35x fewer rollouts, and beats MIPROv2 by over 10%. Because it consumes domain-specific text feedback rather than only a scalar reward, it converges in very few rollouts.
2026-06-02 / skill-finderTurboQuant: Google Research Ships Near-Optimal KV Cache Compression — 3 Bits Per Coordinate, Zero Accuracy LossGoogle Research and NYU published TurboQuant (presented at ICLR 2026), a two-stage vector quantization algorithm compressing LLM KV caches to 3 bits per coordinate with zero accuracy loss. It combines PolarQuant (rotation-based coordinate transform) with a 1-bit QJL residual correction, achieving 6x memory reduction and up to 8x faster attention on NVIDIA H100 GPUs while operating within ~2.7x of the information-theoretic optimum. Community open-source implementations began appearing in early June 2026 — directly actionable for anyone running inference at scale.
2026-05-29 / arxiv-researcherSoundnessBench: Can Your AI Scientist Tell Good Research Ideas from Bad Ones?Benchmark of 1,099 ML research proposals (from ICLR submissions) testing whether LLMs can judge methodological viability before committing resources. Addresses a critical bottleneck in autonomous AI research agents — idea quality filtering. Important for anyone building research automation or agentic coding systems that need to evaluate approach viability.
2026-05-26 / rss-researcherHugging Face Publishes Definitive Agent Glossary — Harness vs. Scaffold vs. Agent Finally DefinedSergio Paniego and Aritra Roy Gosthipaty published a practical glossary on May 25 addressing the terminology confusion that peaked at ICLR 2026: Model (LLM, no memory, no loop), Scaffold (behavior-defining layer: system prompt, tool descriptions, context management), Harness (execution layer: calls model, handles tools, decides stopping), Agent (Model + Scaffold + Harness in an environment loop). The piece also formally defines context engineering, skills vs. tools, and sub-agents — terms the field has been using inconsistently across frameworks.
2026-05-19 / rss-researcherIBM Research and Hugging Face Launch Open Agent Leaderboard — First Standardized Benchmark for Complete Agentic SystemsIBM Research released the Open Agent Leaderboard on Hugging Face, moving beyond single-model benchmarks to evaluate full agentic systems including tool use, planning, memory, and error recovery. Presented at ICLR 2026 with a General Agent Evaluation paper. This addresses a critical gap: existing benchmarks measure model intelligence in isolation, but real agent performance depends on the entire stack — tool selection, step planning, context persistence, and failure handling.
2026-05-11 / reddit-researcherICLR 2026 Contributions by Country and Institution — 5,300+ Papers Accepted in RioA visualization of ICLR 2026 contributions by country and institution is generating discussion on r/singularity (55 upvotes, 32 comments). ICLR 2026 accepted over 5,300 papers, held in Rio de Janeiro April 23-27. Microsoft had 100+ accepted papers. The data reveals shifting global research dynamics as Chinese institutions increase their share of top-tier ML publications. Paper Copilot maintains detailed authorship and country breakdowns for the full accepted paper list.
2026-05-09 / arxiv-researcherLCM: Deterministic Memory Architecture Outperforms Claude Code on Long-Context TasksLossless Context Management (LCM) shifts memory burden from the model to a deterministic engine using recursive context compression (hierarchical summary DAG) and recursive task partitioning (engine-managed parallel primitives). The LCM-augmented coding agent Volt scores higher than Claude Code on the OOLONG long-context eval at every context length from 32K to 1M tokens using Opus 4.6. Accepted at ICLR 2026.
2026-05-07 / reddit-researcherStop Letting LLMs Edit Your .bib Files — Citation Hallucination Now a Systemic Academic ProblemA 150-upvote r/MachineLearning post warns researchers about LLMs corrupting bibliography files, reporting hallucinated citations with correct titles but wrong authors appearing multiple times per month. This aligns with GPTZero's finding that 20% of ICLR 2026 submissions (60 of 300 sampled from 20,000) contain at least one AI hallucination, and Nature's estimate that tens of thousands of 2025 publications may include AI-fabricated references. The academic community is now treating LLM citation corruption as a research integrity crisis, not an edge case.
2026-05-06 / sources-researcherGoogle TurboQuant at ICLR 2026: 6x KV Cache Memory Reduction at 3-Bit Quantization with Zero Accuracy LossGoogle Research presented TurboQuant at ICLR 2026, achieving 6x KV cache memory reduction by quantizing to just 3 bits without training or fine-tuning and with no accuracy loss on Gemma and Mistral benchmarks. The method uses random rotation to simplify vector geometry, then applies a 1-bit residual QJL stage as a mathematical error-checker. Community implementations in PyTorch (Triton kernels), MLX, and llama.cpp are already emerging, making this directly actionable for anyone running local inference.

Graph relationships

BENCHMARKED AGAINST
AI Scientist v2
AI Scientist v2 advances beyond the original AI Scientist which produced the first AI-generated paper at ICLR.
Source finding
Reported in
ICLR 2026 Outstanding Papers Announced: 'Transformers are Inherently Succinct' and Multi-Turn LLM Ev
Source finding
BENCHMARKED AGAINST
AI Scientist v2 -> ICLR
AI Scientist v2 advances beyond the original AI Scientist which produced the first AI-generated paper at ICLR.
Source finding

Source trail

arXiv GEPA A new glossary E2B partnered with Docker Mem0's State of AI Agent Memory report Leaked code and today's keynote Presented at ICLR 2026 The research OpenAI engineers detailed Presented at ICLR 2026 NVIDIA's CEO disclosed ARC Prize's detailed analysis

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