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Showing 1-20 of 29 claims in topic "reasoning" of type "critique"

reasoning
critique
Bearish
academic

Traditional inference-time scaling methods rely on repeated generation or external verification, which is a limitation

"these methods typically rely on repeated generation or external verification"
Computation and Language
8/30/2026
Confidence: 80%Source
2
Page 1 of 2Next
reasoning
critique
Neutral
independent

Qwen 3.8 27B overthinks tasks even when explicitly instructed not to

"I tried "render an svg of five intersecting squares. don't overthink this" at one point and yeah..."
Simon Willison
8/28/2026
Confidence: 85%Source
reasoning
critique
Bearish
critic

ChatGPT produces impossible chess positions and inconsistent piece sizes, demonstrating reasoning limitations

Gary Marcus
8/8/2026
Confidence: 90%Source
reasoning
critique
Bearish
critic

Commercial LLMs still can't play chess anywhere near as well as serious players, except by calling external tools, three years after initial concerns were raised

Gary Marcus
8/8/2026
Confidence: 80%Source
reasoning
critique
Bearish
critic

Success on math problems does not guarantee success in other AI domains because math can heavily leverage symbolic verification and formally generated synthetic data

Gary Marcus
8/3/2026
Confidence: 90%Source
reasoning
critique
Bearish
critic

People are committing the fallacy of composition by thinking a system great at certain math problems is great at all math, science, or everything

Gary Marcus
8/3/2026
Confidence: 85%Source
reasoning
critique
Bearish
critic

The AGI-is-near community repeatedly commits the fallacy of composition with every AI advance

Gary Marcus
8/3/2026
Confidence: 80%Source
reasoning
critique
Bearish
critic

LLMs aren't close to doing real discovery, according to yet another paper

Gary Marcus
8/2/2026
Confidence: 75%Source
reasoning
critique
Bearish
critic

The approach of domain-specific engineering for AI is a regression to 1980s techniques rather than progress toward AGI

Gary Marcus
8/2/2026
Confidence: 70%Source
reasoning
critique
Bearish
critic

OpenAI's reasoning advances rely heavily on domain-specific data augmentation and verification, not general intelligence

Gary Marcus
8/2/2026
Confidence: 70%Source
reasoning
critique
Bearish
critic

Reasoning models work better in math than other domains due to easier verification in those domains, not domain-general capabilities

Gary Marcus
8/2/2026
Confidence: 80%Source
reasoning
critique
Bearish
critic

Claims about a golden age of science from Astra are a leap of faith and overgeneralization from formal to difficult-to-formalize problems

Gary Marcus
8/2/2026
Confidence: 80%Source
reasoning
critique
Bearish
critic

People are leaping to conclusions about Astra's capabilities without evidence of generality to non-formal problems

Gary Marcus
8/2/2026
Confidence: 90%Source
reasoning
critique
Bearish
critic

Astra has not yet solved significant open-world problems outside of formal verification

Gary Marcus
8/2/2026
Confidence: 80%Source
reasoning
critique
Bearish
academic

Existing early-exit gates for diffusion language models fire prematurely on long chain-of-thought outputs whose answers stabilize only near the end

Computation and Language
8/2/2026
Confidence: 75%Source
reasoning
critique
Bearish
academic

Existing visual-latent reasoning methods fail to fully internalize the abstract reasoning process induced by multimodal Chain-of-Thought

Computer Vision
8/2/2026
Confidence: 75%Source
reasoning
critique
Bearish
academic

Existing pre-rollout methods struggle to balance exploitation and exploration in prompt selection

Computation and Language
8/1/2026
Confidence: 75%Source
reasoning
critique
Bearish
academic

LLM initial outputs for SPARQL generation remain unreliable - generated queries may be executable yet semantically misaligned with input questions

Computation and Language
8/1/2026
Confidence: 90%Source
reasoning
critique
Bearish
critic

It's unclear whether Astra can solve all math problems, let alone problems in open-ended, less formalizable domains

Gary Marcus
8/1/2026
Confidence: 75%Source
reasoning
critique
Bearish
critic

Current commercial large language models perform worse at chess than a 7-year-old Kasparov would have

Gary Marcus
7/29/2026
Confidence: 85%Source

Pipeline data may be stale or degraded.

Last synthesis: 2026-09-20. 8,949 pending.